Machine Learning Science

Amazon’s global talent is incredibly complex with unique problems to be solved for each line of business. Global Talent Management (GTM) is centrally responsible for managing and evolving Amazon’s human capital through intelligent talent products and processes. GTM Science is a growing interdisciplinary science team within GTM that develops science products and services to facilitate Amazon’s growth and development of talent across all of our businesses and locations around the world. Our vision in GTM Science is to use machine learning and Generative AI to scalably solve organizational challenges focused on talent movement, talent differentiation, employee-role matching, promotion processes, organizational design and succession planning, diversity and inclusion, and new areas that address the evolving needs of our diverse employee base. We are looking for an experienced ML/AI scientist to work on talent science products that draw from a range of fields such as algorithmic fairness, natural language processing, supervised and unsupervised learning, recommendation systems, machine learning on graphs, reinforcement learning and others on rich and novel datasets. The role has high visibility to senior Amazon business leaders and involves working with other scientists, and partnering with engineering and product teams to integrate these models into production systems. As an applied scientist in GTM Science, you will have the opportunity to work on exciting problems in one of the most innovative applications of science in the People Experience and Technology space. You will help to solve high impact business problems in an unconventional domain, and be encouraged to patent and publish your contributions. If this kind of work excites you, reach out to us to find out more! Key Responsibilities · Design and implement models, science-based product ideas and features, project plans and communicate with stakeholders. · Develop fair predictive models to understand important business and people-centered outcomes · Productionize ML and science models at the scale of Amazon BASIC QUALIFICATIONS- 3+ years of building models for business application experience- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- Experience programming in Java, C++, Python or related language- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing ...

Live Playback and Operations organization owns the live and 24/7 linear channel playback experience from content ingestion and signal acquisition, encoding (H.264/AVC, H.265/HEVC, AV1 etc) and streaming technologies (DASH, HLS, Smooth streaming, Low Latency), feature development (time shifted viewing, replays) to content distribution and delivery (CDN capacity management & load balancing) to the end customer for Prime Video. In addition, the organization handles the D2C (direct to consumer) app and Media Asset delivery for ~50 affiliates for MGM+. To run everything end-to-end at Amazon scale the org owns operations (active monitoring and incident response), instrumentation, infrastructure (on-premise & cloud encoders, direct connects, transport fiber, satellite), and tooling for these areas. Prime Video streams thousands of Amazon produced and third party live events per year in addition to thousands of linear stations globally. We achieve that with high-availability, low-latency, using different formats on approximately 1 billion devices, and do that for millions of customers with the best possible audio-video experience and frugal use of infrastructure and people. This is made possible through the use of advanced technology and science to automate operations, high judgment decision support systems and the infrastructure to deliver complex services simply, reliably and consistently. The Principal Applied Scientist leads innovation across a broad range of specialist areas. These include use of AI for routing content through our vast video delivery network, optimization of video operations, automation of signal processing, identification of defects and anomalies, predicting granular delivery capacity needs using public and private data, and much more. We have advanced capabilities in dedicated groups for low latency content delivery and computer vision quality analysis. Our organization is globally dispersed with an existing science group that has research collaborations with multiple US and European Universities, science publishing, contributions to industry standards and patents. The leader in this role will grow our science broadly across the organization, opening opportunities for innovation and use of cutting-edge science in areas where we see the potential to make significant impact to the service we provide to our customers and how we do that efficiently and effectively at Amazon scale.The scope of the role is broad and reports into the Director of the organization with the intention of steering our science strategy across a wide range of areas. This includes spotting opportunities, connecting with science and engineering leaders across Amazon. It is also required that the leader brings industry and university research context into the organization. The technology landscape changes fast and we make careful choices to balance vendor partnership along with self-build decisions to trade-off moving fast with owning core capabilities. The problems and challenges we face tomorrow may be quite different from those today, and the technology we need to innovate for our customers to go faster, increase our quality, and expand the range of products we provide to customers. The Principal is a key advisor to the Director and leadership team of the organization with the skills to communicate complex subjects simply both orally and in written form to influence our strategic and tactical decisions. You probe assumptions, illuminate pitfalls, bring clarity, and generate shared understanding on science topics. As an Applied Scientist, it is a 'hands-on' science leadership role, and requires opining on decisions that affect the way we create, build, and evaluate scientific solutions. Your views are influential in which research directions we invest in, the universities we collaborate with, and the outcome results. You grow other science leaders, mentoring and coaching them and develop science knowledge and application widely across the organization through educating leaders at multiple levels. You acquire expertise yourself to keep across trends and steer Prime Video in the best direction to invest and the benefits that will accrue from that. Your influence stretches across multiple, diverse teams, globally, and across organizational boundaries. Our science overall is stronger, our understanding of science topics is deeper and broader, and the programs we invest in generate impactful outcomes through your leadership.The role expects you to have a direct science output yourself in a strategic area, connecting with professors at leading universities, speaking and representing Amazon at conferences and industry events and influencing industry standard bodies. You are a thought leader and represent us on specific topics. You are connected with industry and standardization bodies and recognized in those communities. You publish, co-author, and review publications and secure our intellectual property through patents. Key job responsibilitiesThe Playback Development & Operations Principal Scientist is a subject matter expert recognized as a thought leader in a particular science discipline at a global level. For instance, you serve as an Area Chair at peer-reviewed conferences or as a senior program committee member. The role requires connection with internal and external research groups and you are expected to be active in the academic community and have relationships with multiple universities. Your track record includes research, publications, or intellectual property, and application of that domain expertise into real-world problems. The role expects that you will continue to publish in top-ranking journals and present at leading conferences. As a trusted advisor to senior leadership, you are an expert in state-of-the-art methodologies in at least one area of computer science, natural language processing, computer vision, video signal processing, Gen AI, content distribution, networking or other similar topics. As the senior science leader in a large organization, you will develop talent in Prime Video, through involvement in the hiring process, annual evaluations, and promotion assessments. You will develop other science leaders and have a background of growing multiple other experts to an advanced level, perhaps as a PhD advisor or as an industry leader. You have prior experience of getting technology across the line, and have written critical path code or algorithms in the past, and you could be hands on and own most complex and key algorithms when necessary. You understand the concerns of both software engineers and are familiar with research methods used in modern science. In current and previous roles, you have examples where you delivered scientifically complex solutions into production that are innovative and impactful. You can articulate those problems clearly, communicating core science concepts simply, and the resulting benefits. You are up to date with modern trends in compute science. You can speak confidently and influence opinion both at VP level and with junior engineers on the application and opportunities of Machine Learning and Generative AI. You are familiar and have hands-on experience using large language models, transformer architectures, and recent innovations. Ideally, you are also familiar with an aspect of audio-video signal processing, computer vision, or networking/media distribution technology and research. You will prepare and deliver artifacts that set the standard for Prime Video science leadership and engineering excellence. Your science writing and where applicable algorithms, analysis, and research results serve as example within the organization. The research you lead and influence will have results that are demonstrated in service/product features and efficiencies in operations. You collaborate effectively with other leaders to get things done. Your involvement makes science easier to generate impact and saves effort for the organization as a whole to progress our objectives. You do that through advising senior leaders and bringing understanding to complex subjects. You move fast, both to resolve ambiguity and bring innovative solutions to intrinsically hard, previously unsolved problems. To do that, you identify opportunities and convince other leaders by bringing them along with your ideas. You use metrics, data, and analysis to make informed decisions. You lead research that takes balanced risks that inform our future. You not only dive into the immediate pain points but also set the long term science roadmap and vision for the next 3-5 years.BASIC QUALIFICATIONS* PhD with applied research experience in Computer Science or in a highly quantitative field* Evidence of Science/Engineering publications in relevant journals or conferences with more than one as first author * Examples of sourcing funding / creating research relationships with universities or other institutions* Experience of building machine learning models for business application* Background of programming in Java, C++, Python or related language* Theoretical understanding of broad machine learning concepts, with deep and demonstrable expertise in at least one topic or application of machine learning* Conversant with current approaches to generative AI, large language models and their applications ...

Are you passionate about automation, optimization, knowledge extraction, and artificial intelligence through the use of Machine Learning, Computer Vision, Optimization, Natural Language Processing, and Recommender systems? We have a team of experienced scientists with a critical business mission making revolutionary leaps forward in these spaces. On this team you will work with large multimodal datasets to build generative and discriminative models for optimizing large-scale manufacturing and fulfillment processes, analyze and model customer reading behavior to measure engagement and detect risks, and build AI-based systems for helping indie authors make their businesses successful. This will involve combining methods from several science domains with domain knowledge across multiple businesses into sophisticated ML workflows. Our team has mature areas and green-field opportunities. We offer scientific autonomy, value end-to-end ownership, and have a strong customer-focused culture.As an Applied Scientist at Amazon, you will connect with world leaders in your field working on similar problems. You will be working with large distributed systems of data and providing technical leadership to the product managers, teams, and organizations building machine learning solutions. You will be tackling Machine Learning challenges in Supervised, Unsupervised, and Semi-supervised Learning; utilizing modern methods such as deep learning and classical methods from statistical learning theory, detection, estimation. Senior Applied Scientists are specialists with the deep expertise to drive the scientific vision for our products. They are externally aware of the state-of-the-art in their respective field of expertise and are constantly focused on advancing that state-of-the-art for improving Amazon’s products and services. Come join us as we revolutionize the book industry and deliver an amazing experience to our Kindle authors and readers.Key job responsibilitiesGreat candidates for this position will be experts in the areas of data science, machine learning, computer vision, optimization, NLP, or statistics. You will have hands-on experience with multiple science initiatives as well as be able to balance technical leadership with strong business judgment to make the right decisions about technology, models and methodological choices. You will strive for simplicity, and demonstrate significant creativity and high judgment.About the teamKindle Direct Publishing (KDP) and Print On Demand (POD) have empowered a new wave of self-motivated creators, tearing down barriers that once blocked writers from reaching readers. Our team builds rich applications and systems that empower anyone to realize their dream of becoming a published author. We strive to provide an experience that is powerful, yet simple to use and accessible to all. We focus on building systems that enable authors to design high quality digital and print books, reaching readers all around the world. This role will help ensure we maintain the trust of both our Authors and Readers by ensuring all books published to Amazon meet our standards.BASIC QUALIFICATIONS- 3+ years of building models for business application experience- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- Experience in patents or publications at top-tier peer-reviewed conferences or journals- Experience programming in Java, C++, Python or related language- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing ...

Amazon’s Customer Behavior Analytics org is looking for an Applied Scientist to spearhead the rapid growth of our Marketing Measurement solutions. The team focuses on building scalable ML and causal inference solutions to estimate the effectiveness of Amazon marketing efforts and provide actionable insights to the various marketing teams within Amazon. This is a high-impact role with opportunities to develop systems that affect investments to the size of billions of dollars. We work closely with business stakeholders and strive to continuously produce tangible impact on the company’s strategic and tactical planning and operations. A successful candidate will be a self-starter, comfortable with ambiguity, able to think big and be creative, while still paying careful attention to detail. You should be able to translate how data represents the customer journey, be comfortable dealing with large and complex data sets, and have experience using machine/deep learning at scale to solve business problems. You should have strong analytical and communication skills, be able to work with product managers and software teams to define key business questions and work with the analytics team to solve them. You will apply your expertise in ML/DL, statistics, and data-wrangling to identify opportunities for further research and to provide insights that drive larger initiatives. You will join a highly collaborative and diverse working environment that will empower you to shape the future of Amazon marketing, as well allow you to be part of the large science community within the Customer Behavior Analytics (CBA) organization.Key job responsibilitiesThe main responsibilities for this position include: - Apply your expertise in ML/DL and statistical modeling to develop solutions and systems that describe how Amazon’s marketing campaigns impact customers’ actions - Own the end-to-end development of novel causal inference models that address the most pressing needs of our business stakeholders and help guide their future actions - Improve upon and simplify our existing solutions and frameworks - Review and audit modeling processes and results from other scientists, both junior and senior - Work with marketing leadership to align our measurement plan with business strategy - Formalize assumptions about how our models are expected to behave and explain why they are reasonable - Identify new opportunities that are suggested by the data insights - Bring a department-wide perspective into decision making - Develop and document scientific research to be shared with the greater science community at AmazonAbout the teamThe Customer Behavior Analytics (CBA) organization owns Amazon’s insights pipeline, from data collection to deep analytics. We aspire to be the place where Amazon teams come for answers, a trusted source for data and insights that empower our systems and business leaders to make better decisions. Our outputs shape Amazon product and marketing teams’ decisions and thus how Amazon customers see, use, and value their experience. BASIC QUALIFICATIONS- 3+ years of building models for business application experience- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- Experience programming in Java, C++, Python or related language- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing ...

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising products that drive discovery and sales. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day!The Customer - Advertiser Success & Insights (CASI) team is seeking an Applied Scientist to help increase the effectiveness of online advertising. You will leverage computer vision, generative AI, natural language processing, casual inference, and machine learning to enhance the customer experience with online advertising. In this role, you will collaborate closely with business leaders, stakeholders, and cross-functional teams to drive success for our customers through data-driven solutions. This is an excellent opportunity for a technically-minded individual to make a tangible impact on the online advertising landscape. The role offers the chance to work with state-of-the-art technologies and contribute to the evolution of a rapidly changing industry.Key job responsibilitiesAs an Applied Scientist in CASI, you will:-> Shape the science roadmap for CASI, fostering a culture of data-driven decision-making.-> Deliver significant business impact through advanced ML models, generative AI, and cutting-edge causal inference methodologies.-> Produce and deliver models that help drive best-in-class customer experiences and build systems that allow us to deploy these models to production with low latency and high throughput.-> Collaborate with cross-functional teams, including software engineers, data scientists, and product managers, to define project requirements, establish success metrics, and deliver high-quality solutions.-> Research new and innovative machine learning approaches.BASIC QUALIFICATIONS- 3+ years of building models for business application experience- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- Experience in patents or publications at top-tier peer-reviewed conferences or journals- Experience programming in Java, C++, Python or related language- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing ...

Amazon AI is looking for an Applied Scientist to join our science team in the area of Multimodal Learning, Large Language Models, Natural Language Processing and Speech/Audio Representation Learning. Our organization develops the science that drives the cloud-based AI services of AWS. Our mission is to put the power of AI into the hands of every developer. We seek to advance the state of the art in machine learning to create services that delight our customers and meet real-world business needs.As an Applied Scientist you will partner with talented scientists and engineers to design, train, test, and deploy machine learning models. You will contribute to innovative features, improve our services based on customer requirements and help maintain a highlyscalable data and model management infrastructure that supports cutting-edge research. You will be responsible for translating business and engineering requirements into deliverables and software products.We are looking for candidates who thrive in an exciting, fast-paced environment and who have a strong personal interest in learning, researching, and creating new technologies with high customer impact.Prior domain knowledge in multimodal learning, unsupervised speech/audio representations, natural language processing, or computer vision is strongly preferred; solid knowledge of fundamentals of statistics, machine learning, and deep learning is required. Candidates should possess strong software engineering skills and several years of industry experience.About the teamAbout AWSDiverse ExperiencesAWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS?Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.Inclusive Team CultureHere at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.Mentorship & Career GrowthWe’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life BalanceWe value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. This team is part of AWS Utility Computing: Utility Computing (UC) AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services.BASIC QUALIFICATIONS- PhD, or Master's degree and 6+ years of applied research experience- 3+ years of building machine learning models for business application experience- Experience programming in Java, C++, Python or related language- Experience with neural deep learning methods and machine learning ...

Amazon's Pricing & Promotions Science is seeking a driven Applied Scientist to harness planet scale multi-modal datasets, and navigate a continuously evolving competitor landscape, in order to regularly generate fresh customer-relevant prices on billions of Amazon and Third Party Seller products worldwide.We are looking for a talented, organized, and customer-focused applied researchers to join our Pricing and Promotions Optimization science group, with a charter to measure, refine, and launch customer-obsessed improvements to our algorithmic pricing and promotion models across all products listed on Amazon.This role requires an individual with exceptional machine learning and reinforcement learning modeling expertise, excellent cross-functional collaboration skills, outstanding business acumen, and an entrepreneurial spirit. We are looking for an experienced innovator, who is a self-starter, comfortable with ambiguity, demonstrates strong attention to detail, and has the ability to work in a fast-paced and ever-changing environment.Key job responsibilities- See the big picture. Understand and influence the long term vision for Amazon's science-based competitive, perception-preserving pricing techniques- Build strong collaborations. Partner with product, engineering, and science teams within Pricing & Promotions to deploy machine learning price estimation and error correction solutions at Amazon scale- Stay informed. Establish mechanisms to stay up to date on latest scientific advancements in machine learning, neural networks, natural language processing, probabilistic forecasting, and multi-objective optimization techniques. Identify opportunities to apply them to relevant Pricing & Promotions business problems- Keep innovating for our customers. Foster an environment that promotes rapid experimentation, continuous learning, and incremental value delivery.- Successfully execute & deliver. Apply your exceptional technical machine learning expertise to incrementally move the needle on some of our hardest pricing problems.A day in the lifeWe are hiring an applied scientist to drive our pricing optimization initiatives. The Price Optimization science team drives cross-domain and cross-system improvements through:* invent and deliver price optimization, simulation, and competitiveness tools for Sellers. * shape and extend our RL optimization platform - a pricing centric tool that automates the optimization of various system parameters and price inputs. * Promotion optimization initiatives exploring CX, discount amount, and cross-product optimization opportunities.* Identifying opportunities to optimally price across systems and contexts (marketplaces, request types, event periods)Price is a highly relevant input into many partner-team architectures, and is highly relevant to the customer, therefore this role creates the opportunity to drive extremely large impact (measured in Bs not Ms), but demands careful thought and clear communication.About the teamAbout the team: the Pricing Discovery and Optimization team within P2 Science owns price quality, discovery and discount optimization initiatives, including criteria for internal price matching, price discovery into search, p13N and SP, pricing bandits, and Promotion type optimization. We leverage planet scale data on billions of Amazon and external competitor products to build advanced optimization models for pricing, elasticity estimation, product substitutability, and optimization. We preserve long term customer trust by ensuring Amazon's prices are always competitive and error free.BASIC QUALIFICATIONS- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- Experience programming in Java, C++, Python or related language- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing- 2+ years of hands-on predictive modeling and large data analysis experience- Experience in solving business problems through machine learning, data mining and statistical algorithms ...

Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads.Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience.As a Prime Video technologist, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people.We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you!Key job responsibilitiesAs a highly experienced and seasoned science leader, you will apply state of the art natural language processing and computer vision research to video centric digital media, while also responsible for creating and maintaining the best environment for applied science in order to recruit, retain and develop top talent. You will lead the research direction for a team of deeply talented applied scientists, creating the roadmaps for forward-looking research and communicate them effectively to senior leadership. You will also hire and develop applied scientists - growing the team to meet the evolving needs of our customers.BASIC QUALIFICATIONS- 3+ years of building models for business application experience- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- Experience programming in Java, C++, Python or related language- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing ...

Revolutionize the Future of FinTech with Worldwide Installments Science & Engineering!Are you ready to shape the future of global finance? Join the elite Worldwide Installments team within Amazon Payments (AP) and be at the forefront of innovation where cutting-edge machine learning, advanced econometrics, and state-of-the-art technology converge to redefine the financial landscape.🌟 Our Mission: To create payment experiences and financial services that are unparalleled in trust, value, and ease of use – accessible from anywhere, anytime.🚀 What We Offer:- Unprecedented growth in a rapidly expanding market- Continuous innovation with market-leading features- Groundbreaking ML solutions that directly impact customers🧠 Your Playground:- Access to Amazon's vast data ecosystem- Cutting-edge probabilistic modeling- Real-time decision-making systems affecting millions- Global-scale experimentation and optimization🌍 Your Impact:- Influence the purchasing experience of hundreds of millions of consumers worldwide- Work on the most sophisticated FinTech challenges in the BNPL/Installment space- Collaborate with top-tier professionals across Amazon's global network🔍 We're Seeking:An exceptional talent to spearhead our ML roadmap. This role is your gateway to working with one of the world's most complex and extensive data environments. You'll be at the nexus of data, strategy, and innovation, directly influencing Amazon's global financial strategies.💼 Your Arsenal:- Mastery in managing and deriving insights from massive datasets- Deep expertise in scalable data mining and financial modeling- Strong business acumen and superior communication skills- Ability to translate complex data into actionable business strategies🏆 Why This Role is Unmatched:This position offers unparalleled exposure to the pinnacle of FinTech innovation. You'll be working on challenges that no other company in the world can offer, with resources and scale that are truly unique to Amazon.Join us in revolutionizing global finance. Your expertise could shape how millions of people interact with money in the digital age. This isn't just a job – it's a chance to leave your mark on the future of financial technology.Are you ready to redefine what's possible in FinTech? Apply now and let's build the future together!BASIC QUALIFICATIONS- 5+ years of building quantitative solutions as a scientist or science manager experience- 2+ years of scientists or machine learning engineers management experience- 5+ years of applying statistical models for large-scale application and building automated analytical systems experience- PhD in computer science, mathematics, statistics, machine learning or equivalent quantitative field- Knowledge of Python or R or other scripting language ...

Our team drives innovation for the onsite retail shopping site publisher. We collaborate and influence the advertising science community at Amazon across the entire Ads stack— sourcing and ranking ads, bidding into and pricing in the ads auction, experimentation design to measure causal impact of showing ads on shoppers and Amazon vendors, creative development with GenAI, and more. If you’re interested in joining a unique, highly respected advertising group with a relentless focus on the customer, you’ve come to the right place. As we continue building to out our team, we are looking for a Principal Applied Scientist, to lead research, design, experiment and implementation of cutting edge algorithms for complex Stores Display publisher use cases. You will collaborate with Amazon demand programs and front-end teams to influence how the entire advertising stack works end-to-end. You will work with business and finance teams to design experiments that inform tradeoffs across advertiser and shopper goals. You will work collaboratively with software engineers, data engineers, and other scientists on the team to deploy production algorithms that support the billions of ad auctions run daily and set a high bar for science and engineering excellence. This is a rare opportunity to be a foundational member with huge potential for impact and innovating new user experiences at Amazon. Why you will love this opportunity: Despite being part of a large business, we embrace a start-up mentality. This is an opportunity for massive impact and affords a lot of autonomy.Impact and Career Growth: You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding.Key job responsibilitiesAs a Principal Applied Scientist on this team, you will:- Be the technical science leader on the org; leading efforts within his team and across other teams.- Perform hands-on analysis and modeling of enormous data sets to develop insights that increase traffic monetization and retail merchandise sales, without compromising the shopper experience.- Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity.- Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models.- Run A/B experiments, gather data, and perform statistical analysis.- Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.- Research new and innovative machine learning approaches.- Recruit Applied Scientists to the team and provide mentorship.About the teamAmazon Advertising operates at the intersection of eCommerce and advertising, offering a rich array of digital advertising solutions with the goal of helping our customers find and discover anything they want to buy. We help advertisers reach Amazon customers on some of the most valued advertising real estate on the internet on the Amazon.com store. We start with the customer and work backwards in everything we do, including advertising. BASIC QUALIFICATIONS* 10+ years of building models for business application experience or applied research in industry settings* PhD, or Master's degree in CS, Statistics,, ML or related fields* Experience programming in Python or related language* Experience in any of the following areas: algorithms and data structures, optimal control, numerical optimization, data mining, parallel and distributed computing, high-performance computing ...

How often have you had an opportunity to be an early member of a team that is tasked with solving a huge customer need through disruptive, innovative technology, reinventing an industry? Do you apply Machine Learning to big data problems? Are you excited by analyzing and modeling terabytes of data that solve real world problems? We love data and have lots of it. We’re looking for an engineer capable of using machine learning and statistical techniques to create solutions for non-trivial, and arguably, unsolved problems. We are working on revolutionizing the way Amazonians work and collaborate. Our team is on a mission to transform productivity through the power of advanced generative AI technologies. In pursuit of this mission we are seeking a motivated Machine Learning Engineer to join our team. The successful candidate will be responsible for developing, implementing, and optimizing machine learning models that will drive our generative AI initiative. This role involves close collaboration with data scientists, software engineers, and UX/UI designers to create a seamless and context-aware AI solution that enhances productivity across various user personas within Amazon.You will join a highly motivated, collaborative and fun-loving team with an entrepreneurial spirit and bias for action. The role will challenge you to think differently, hone your skills, and invent at scale. We're looking for engineers who obsess over technical details but can delight customers by continually learning and building the right products. You will help to invent the future of advertising.Technical Skills needed:-- Programming Languages: Proficiency in Python, including libraries such as TensorFlow, PyTorch, and scikit-learn.- Experience with R or Java is a plus.- Machine Learning and AI: Strong understanding of machine learning algorithms and frameworks. - Experience with natural language processing (NLP) techniques and models.- Familiarity with reinforcement learning and its applications.- Knowledge of supervised and unsupervised learning methods.- Data Preprocessing and Analysis: Expertise in data cleaning, normalization, and transformation. Ability to perform feature engineering and selection. Proficiency in data analysis tools and techniques.- Model Development and Evaluation: Experience in developing, training, and fine-tuning machine learning models. Knowledge of model evaluation metrics such as accuracy, precision, recall, F1-score, and AUC-ROC. Familiarity with cross-validation techniques.- Big Data Technologies: Experience with big data tools and frameworks like Hadoop, Spark, or Kafka. Proficiency in handling large datasets and optimizing data pipelines.- API and Microservices Development: Experience in developing and deploying RESTful APIs. Familiarity with microservices architecture and related technologies.- Cloud Platforms: Experience with cloud platforms such as AWS. Proficiency in using cloud-based machine learning and data storage services.- Security and Privacy: Understanding of data privacy regulations and best practices. Experience with data anonymization techniques and secure data handling.Key job responsibilities1. Model Development: Design, develop, and implement machine learning models, particularly focusing on natural language processing (NLP) and reinforcement learning techniques.2. Data Preprocessing: Perform data cleaning, normalization, and feature engineering to prepare datasets for model training.3. Model Training: Train and fine-tune machine learning models to achieve high accuracy and robustness.4. Integration: Work with the software engineering team to integrate ML models into the middleware that interfaces with Amazon’s GenAI offerings.5. Performance Evaluation: Use cross-validation and various performance metrics (e.g., precision, recall, F1-score) to evaluate model performance and ensure their reliability.6. Continuous Improvement: Implement reinforcement learning strategies to ensure the AI system continuously learns and improves from user interactions.7. Collaboration: Collaborate with data scientists, software engineers, and UX/UI designers to ensure the models meet user requirements and integrate seamlessly with existing tools.8. Documentation: Document model architectures, training processes, and evaluation results to ensure transparency and reproducibility.A day in the life - Spending time designing and implementing machine learning models, with a particular focus on NLP and reinforcement learning applications - Conducting data preprocessing tasks including cleaning datasets, normalizing values, and engineering features to prepare data for model training - Running model training sessions and fine-tuning parameters to optimize model performance - Working closely with software engineers to integrate machine learning models into Amazon's GenAI middleware systems- Testing and evaluating model performance using various metrics and cross-validation techniques- Implementing and monitoring reinforcement learning mechanisms to capture user feedback and improve system performance- Attending collaboration sessions with cross-functional team members including data scientists, software engineers, and UX/UI designers- Maintaining detailed documentation of model architectures, training procedures, and evaluation resultsAbout the teamWe are a team part of Enterprise Engineering at Amazon focused on revolutionizing how Amazonians work and collaborate through advanced generative AI technologies. Our mission is to transform productivity across the organization by developing AI solutions. We are highly motivated, collaborative, and maintain an entrepreneurial spirit with a bias for action.Our team brings together diverse talents including data scientists, machine learning engineers, software engineers, and UX/UI designers, all working in concert to create innovative AI solutions. We value technical excellence while maintaining a fun-loving atmosphere that encourages creativity and innovation.We operate at the forefront of AI technology, tackling complex challenges that require innovative thinking and technical expertise. Our team culture emphasizes continuous learning, invention at scale, and a deep commitment to delighting our customers through transformative solutions. If you're passionate about pushing the boundaries of what's possible with AI while working in a collaborative, fast-paced environment, you'll find yourself at home with our team.BASIC QUALIFICATIONS- 2+ years of data scientist experience- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience- Experience applying theoretical models in an applied environment ...

Amazon's Global Logistics (GL) team is seeking an experienced Senior Applied Scientist to research and deploy production solutions for transportation Pricing, Downstream Impact (DSI), and Network Flow. In this role, you will contribute to our vision of offering best-in-class global transportation capabilities for FBA Sellers and Retail Vendors, enabling them to ship efficiently from their locations to Amazon warehouses worldwide. Your work will help lower the cost structure for Amazon and our shippers, while also improving selection and availability for Amazon's consumers by simplifying complex global supply chains and replenishing inventories faster.Key job responsibilities- Collaborate closely with product managers, research scientists, operations leaders, and technical leadership to build cutting-edge transportation capabilities.- Analyze large datasets, develop end-to-end workflows, prototype optimization and machine learning models, and launch production-ready solutions.- Communicate your research findings and provide scientific guidance to the business, influencing our product strategy and roadmap.- Conduct experimental research that will inform future investment areas for the transportation business.A day in the life- Reviewing and refining the requirements for a new transportation pricing model with the product management team.- Conducting exploratory data analysis to uncover insights that can inform the design of the pricing algorithm.- Building and testing optimization prototypes, iterating on the model based on performance metrics.- Presenting your progress and initial findings to senior leadership, soliciting feedback to shape the next phase of development.- Collaborating with the engineering team to ensure a smooth transition of the model into production.About the teamYou will be joining the Network Economics, Research and Data Science (NERDS) Team, which supports GL's transportation business for North America (United States, Canada, and Mexico). The team's research focuses on developing solutions to improve transportation pricing, costs, speed, shipper support, fraud/theft prevention, shipment visibility, and delivery appointment scheduling for Amazon warehouses.Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan Learn more about our benefits here: https://www.amazon.jobs/en/internal/benefits/us-benefits-and-stockBASIC QUALIFICATIONS- 3+ years of building machine learning models or developing algorithms for business application experience- PhD, or Master's degree and 6+ years of applied research experience- Experience programming in Java, C++, Python or related language- Experience with neural deep learning methods and machine learning ...

This is a unique opportunity to join a small, high-impact team working on AI agents for health initiatives. You will collaborate with experts across domains to develop AI solutions to customers. You'll have the chance to work on projects that could significantly impact how individuals manage their daily health and long-term wellness goals.If you're passionate about solving meaningful problems in healthcare through AI, this role is for you. Technically, you'll work on large-scale data processing, algorithm development, and AI agent implementation. You'll have the chance to learn and innovate alongside healthcare experts.In this early-stage initiative, you'll have significant influence on what we build and how we build it. This is an excellent opportunity for high-judgment scientists to demonstrate impact and make key decisions.Key job responsibilitiesImplement state-of-the-art techniques for LLMs and AI agents in health contexts.Develop personalization features for AI agents and invent new methods to tailor health recommendations, interpret individual health data, and provide context-aware wellness guidance.Analyze and experiment with LLM architectures.Contribute to internal knowledge sharing and research papersCollaborate with other teams on Amazon AI health projectsA day in the lifeYou'll work with a cross-disciplinary team to plan and deliver AI-driven health and wellness experiences. You'll shape product features, user experience, and team processes for rapid iteration. Expect to challenge conventional approaches and dive deep into customer problems in this evolving field.BASIC QUALIFICATIONS- 3+ years of building models for business application experience- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- Experience programming in Java, C++, Python or related language- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing ...

We’re working to improve shopping on Amazon using the conversational capabilities of large language models, and are searching for pioneers who are passionate about technology, innovation, and customer experience, and are ready to make a lasting impact on the industry. You'll be working with talented scientists, engineers, and technical program managers (TPM) to innovate on behalf of our customers. If you're fired up about being part of a dynamic, driven team, then this is your moment to join us on this exciting journey!BASIC QUALIFICATIONS- 3+ years of building models for business application experience- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- Experience in patents or publications at top-tier peer-reviewed conferences or journals- Experience programming in Java, C++, Python or related language- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing ...

At AWS, we build and operate AI services responsibly, driving measurable success along multiple Responsible AI dimensions, including safety, fairness, privacy, security, robustness, explainability, and transparency.As a Principal Applied Scientist on this team, you will contribute to:• Understanding in depth the technical and scientific issues related to safety, fairness, privacy, security, robustness, explainability, transparency, and other issues, in both "classical" and generative AI.• Developing new solutions and science best practices in Responsible AI.• Developing our research and innovation agenda.• Defining the strategies, priorities and metrics for technical progress in Responsible AI.• Building and developing the AWS team.• Driving adoption of new science and best practices among service teamsBASIC QUALIFICATIONS• Understanding in depth the technical and scientific issues related to safety, fairness, privacy, security, robustness, explainability, transparency, and other issues, in both "classical" and generative AI.• Developing new solutions and science best practices in Responsible AI.• Developing our research and innovation agenda.• Defining the strategies, priorities and metrics for technical progress in Responsible AI.• Building and developing the AWS team.• Driving adoption of new science and best practices among service teams. ...

The Seller Fees team owns the end-to-end fees experience for two million active third party sellers worldwide. We own the fee technology, fee strategy, seller experience, fee integrity, fee science and data engineering to provide scalable technology to monetize all services available to third-party sellers. We are looking for an Applied Scientist with strong engineering background to join us on improving accuracy in billion-scale fee transactions worldwide and enhancing models to provide better Seller experience with fee services. In this role you will develop large scale deep learning systems to drive the fee calculations that impact hundreds of millions of products from third-party sellers in the Amazon product catalog. You will leverage sophisticated statistical methods, supervised and unsupervised learning models, as well as generative AI that can scale to production requirements worldwide. You will participate in developing models at the intersection of deep learning and causal inference. You will collaborate with other Applied Scientists, Research Scientists, Data Scientists, Economists, Software Developers, and Product Managers. If big and rich data, large scale deep learning and building intelligent systems excites you, we would like you to be on our team!Key job responsibilitiesResponsibilities:. Design measurable and scalable science solutions that can be adopted across stores worldwide with different languages, policy and requirements.· Integrate AI (both generative and symbolic) into compound agentic workflows to transform complex business systems into intelligent ones for both internal and external customers. · Develop large scale classification and prediction models using the rich features of text, image and customer interactions and state-of-the-art techniques.· Research and implement novel machine learning, statistical and econometrics approaches.· Write high quality code and implement scalable models within the production systems.· Stay up to date with relevant scientific publications.· Collaborate with business and software teams both within and outside of the fees organization.BASIC QUALIFICATIONS- 3+ years of building models for business application experience- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- 2+ years of deep learning, computer vision, human robotic interaction, algorithms implementation experience- Experience programming in Java, C++, Python or related language- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing- 2+ years of solving business problems through machine learning, data mining and statistical algorithms experience ...

The AWS Marketplace & Partner Services Science team is hiring an Applied Scientist to develop science products that support AWS initiatives to grow AWS Partners. The team is seeking candidates with strong background in machine learning and engineering, creativity, curiosity, and great business judgment. As an applied scientist on the team, you will work on targeting and lead prioritization related AI/ML products, recommendation systems, and deliver them into the production ecosystem. You are comfortable with ambiguity and have a deep understanding of ML algorithms and an analytical mindset. You are capable of summarizing complex data and models through clear visual and written explanations. You thrive in a collaborative environment and are passionate about learning.Key job responsibilities- Work with scientists, product managers and engineers to deliver high-quality science products- Experiment with large amounts of data to deliver the best possible science solutions- Design, build, and deploy innovative ML solutions to impact AWS Co-Sell initiativesAbout the teamThe AWS Marketplace & Partner Services team is the center of Analytics, Insights, and Science supporting the AWS Specialist Partner Organization on its mission to provide customers with an outstanding experience while working with AWS partners. The Science team supports science models and recommendation systems that are deployed directly to AWS Customers, AWS partners, and internal AWS Sellers. Why AWSAmazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.Inclusive Team CultureHere at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.Work/Life BalanceWe value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.Mentorship and Career GrowthWe’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.Diverse ExperiencesAmazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.BASIC QUALIFICATIONS- PhD, or Master's degree and 4+ years of building machine learning models for business application experience- Experience with data querying languages (e.g., SQL)- Deep knowledge of natural language processing, deep learning, and recommendation systems- Experience programming in Java, Python or related language ...

Are you passionate about applying formal verification, program analysis, constraint-solving, and theorem proving to real world problems? Do you want to create products that help customers? If so, then we have an exciting opportunity for you. In this role, you will interact with internal teams and external customers to understand their requirements. You will apply your knowledge to propose innovative solutions, create software prototypes, and productize prototypes into production systems using software development tools and methodologies. In addition, you will support and scale your solutions to meet the ever growing demand of customer use.Technical Responsibilities:- Interact with various teams to develop an understanding of their security and safety requirements.- Apply the acquired knowledge to build provably correct and performant software to address identified needs.- Perform analysis of the customer systems using tools developed in-house or externally provided.- Create software prototypes to verify and validate the devised solutions methodologies; integrate the prototypes into production systems using standard software development tools and methodologies.Leadership Responsibilities:- Can present and defend company-wide technical decisions to the internal technical community and represent the company effectively at technical conferences.- Functional thought leader, sought after for key tech decisions. Can successfully sell ideas to an executive level decision maker.- Mentors and trains the research scientist community on complex technical issues.BASIC QUALIFICATIONS- Ph.D. degree in Electrical Engineering, Computer Science, Mathematics, or related technical field- At least 7+ years of industrial/academic experience in formal verification, program analysis, constraint-solving, and theorem proving - At least 7+ years of experience with programming languages such as Java, Scala, C/C++, Ruby, or Python and open-source technologies ...

The Amazon Robotics Autonomous Mobility software team develops the autonomy software that powers Proteus, Amazon’s first fully autonomous warehouse robot. We are looking for a Senior Applied Scientist to join our perception and localization team. You will be part of an exceptional group of engineers building the platform and architecture for our onboard mapping, perception, motion planning and control software. In addition, you will collaborate with engineers and scientists across the team to develop and enhance our real-time multi-robot simulation capabilities. Key job responsibilitiesSpecific areas of focus may include (but are not limited too):- Researching, designing, and implementing scientific approaches for sensor calibration, including cameras and LIDARs.- Researching, designing, and implementing scientific approaches for SLAM (simultaneous localization and mapping).- Supporting and improving the large-scale deployment of a SLAM system shared across an autonomous robot fleet.- Evaluating and integrating new sensing modalities into an existing autonomy software stack.- Optimizing runtime performance of autonomy algorithms by exploiting underlying hardware acceleration capabilities.- Building frameworks for large-scale replay and analysis of events in pre-recorded sensor data.- Deliver high quality production level code (C++ or Python) and support systems in production.- Collaborate with other functional teams in a robotics organization.- Collaborate with hardware engineering team members on developing systems from prototyping to production level.- Work with stakeholders across hardware and operations teams to iterate on system design and implementation.A day in the lifeAmazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!About the teamWe are a multi-disciplinary team of collaborative Applied Scientists and Software Engineers with expertise in Computer Vision, SLAM, motion planning and controls. Our mission is to deliver a robust software solution the utilizes state-of-the-art sensor technologies and algorithms to enable safe and efficient operation of autonomous mobile robots throughout the Amazon fulfillment and transportation network. We take this mission seriously and work hard to achieve it, but we have a lot of fun along the way. After all, what's more fun than building robots?BASIC QUALIFICATIONS- Proven experience in robotic perception, SLAM, or computer vision.- M.S. or PhD in Engineering, Sciences, Mathematics or similar fields.- Excellent C++ or python programming skills including debugging, performance analysis, and test design. ...

** This position is open to all candidates in Seattle, WA, NYC and Arlington, VA **Amazon Ads Response Prediction team is your choice, if you want to join a highly motivated, collaborative, and fun-loving team with a strong entrepreneurial spirit and bias for action. We are seeking an experienced and motivated Machine Learning Applied Scientist who loves to innovate at the intersection of customer experience, deep learning, and high-scale machine-learning systems.Amazon Advertising operates at the intersection of eCommerce and advertising, and is investing heavily in building a world-class advertising business. We are defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long-term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products to improve both shopper and advertiser experience. With a broad mandate to experiment and innovate, we grow at an unprecedented rate with a seemingly endless range of new opportunities. We are looking for a talented Machine Learning Applied Scientist for our Amazon Ads Response Prediction team to grow the business. We are providing advanced real-time machine learning services to connect shoppers with right ads on all platforms and surfaces worldwide. Through the deep understanding of both shoppers and products, we help shoppers discover new products they love, be the most efficient way for advertisers to meet their customers, and helps Amazon continuously innovate on behalf of all customers.Key job responsibilitiesAs a Machine Learning Applied Scientist, you will:* Conduct deep data analysis to derive insights to the business, and identify gaps and new opportunities * Develop scalable and effective machine-learning models and optimization strategies to solve business problems * Run regular A/B experiments, gather data, and perform statistical analysis* Work closely with software engineers to deliver end-to-end solutions into production * Improve the scalability, efficiency and automation of large-scale data analytics, model training, deployment and serving * Conduct research on new machine-learning modeling to optimize all aspects of Sponsored Products businessAbout the teamWe are pioneers in applying advanced machine learning and generative AI algorithms in Sponsored Products business. We empower every customer with a customized discovery experiences from back-end optimization (such as customized response prediction models) to front-end CX innovation (such as widgets), to help shoppers feel understood and shop efficiently on and off Amazon.BASIC QUALIFICATIONS- 3+ years of building machine learning models for business application experience- PhD, or Master's degree and 6+ years of applied research experience- Experience programming in Java, C++, Python or related language- Experience with neural deep learning methods and machine learning ...