Machine Learning Science

AWS Analytics is looking for a passionate, inventive Applied Scientist with a strong background in either machine learning, programming languages or databases to help create industry-leading analytics experiences powered by generative AI, machine learning, and program analysis. AWS provides a comprehensive set of analytics services for all data analytics needs and enables organizations of all sizes and industries to reinvent their business with data. From storage and management, data governance, actions, and experiences, AWS offers purpose-built services that provide the best price-performance, scalability, and lowest cost.We are a team dedicated to delivering transformative, science-driven analytics experiences for Amazon customers and having fun doing so. Our leadership team fosters an inclusive team culture and encourages work-life balance to bring out the best in each team member. Collaboration and mentorship are key tenets of our fabric. We are a growing team dedicated to supporting new members achieve their aspirations.Key job responsibilitiesAs part of the AWS Analytics science team you will have the opportunity to apply your skills in machine learning, program analysis, and databases to impact some of the largest analytics services in the industry and their customers. You will innovate by designing and building agent-based solutions orchestrating foundation models, machine learning models, and program analyses to simplify AWS customers’ analytics journey and optimize their cost-performance profile. You will collaborate with a talented team of applied science peers to drive scientific impact and with engineering, product, and business leaders to launch your work in production at Amazon scale.A day in the lifeA mix of the following activities: talking to product leaders and customers to define science features; researching the state of the art and creating science plans to build them; building and rigorously benchmarking the science implementations of such features; partnering with engineering teams to onboard science work and launch it in production; preparing, publishing, and presenting scientific work at top-tier science venues and evangelizing it within the company; upgrading your science knowledge by participating in reading groups and science presentations by internal or external scientists; mentoring applied science interns and science peers in all of the above functions.About the teamDiverse ExperiencesAWS values diverse experiences. Even if you do not meet all of the 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. BASIC QUALIFICATIONS- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field- Experience programming in Java, C++, Python or related language- Experience in patents or publications at top-tier peer-reviewed conferences or journals- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing ...

Unlock the Future with Amazon Science!Calling all visionary minds passionate about the transformative power of machine learning! Amazon is seeking boundary-pushing graduate student scientists who can turn revolutionary theory into awe-inspiring reality. Join our team of visionary scientists and embark on a journey to revolutionize the field by harnessing the power of cutting-edge techniques in bayesian optimization, time series, multi-armed bandits and more. At Amazon, we don't just talk about innovation – we live and breathe it. You'll conducting research into the theory and application of deep reinforcement learning. You will work on some of the most difficult problems in the industry with some of the best product managers, scientists, and software engineers in the industry. You will propose and deploy solutions that will likely draw from a range of scientific areas such as supervised, semi-supervised and unsupervised learning, reinforcement learning, advanced statistical modeling, and graph models.Throughout your journey, you'll have access to unparalleled resources, including state-of-the-art computing infrastructure, cutting-edge research papers, and mentorship from industry luminaries. This immersive experience will not only sharpen your technical skills but also cultivate your ability to think critically, communicate effectively, and thrive in a fast-paced, innovative environment where bold ideas are celebrated.Join us at the forefront of applied science, where your contributions will shape the future of AI and propel humanity forward. Seize this extraordinary opportunity to learn, grow, and leave an indelible mark on the world of technology.Amazon has positions available for Machine Learning Applied Science Internships in, but not limited to Arlington, VA; Bellevue, WA; Boston, MA; New York, NY; Palo Alto, CA; San Diego, CA; Santa Clara, CA; Seattle, WA.Key job responsibilitiesWe are particularly interested in candidates with expertise in: Optimization, Programming/Scripting Languages, Statistics, Reinforcement Learning, Causal Inference, Large Language Models, Time Series, Graph Modeling, Supervised/Unsupervised Learning, Deep Learning, Predictive Modeling In this role, you will work alongside global experts to develop and implement novel, scalable algorithms and modeling techniques that advance the state-of-the-art in areas at the intersection of Reinforcement Learning and Optimization within Machine Learning. You will tackle challenging, groundbreaking research problems on production-scale data, with a focus on developing novel RL algorithms and applying them to complex, real-world challenges.The ideal candidate should possess the ability to work collaboratively with diverse groups and cross-functional teams to solve complex business problems. A successful candidate will be a self-starter, comfortable with ambiguity, with strong attention to detail and the ability to thrive in a fast-paced, ever-changing environment.A day in the life- Develop scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation.- Design, development and evaluation of highly innovative ML models for solving complex business problems.- Research and apply the latest ML techniques and best practices from both academia and industry.- Think about customers and how to improve the customer delivery experience.- Use and analytical techniques to create scalable solutions for business problems. BASIC QUALIFICATIONS- Are enrolled in a PhD- Are 18 years of age or older- Work 40 hours/week minimum and commit to 12 week internship maximum- Can relocate to where the internship is based- Experience programming in Java, C++, Python or related language- Experience with one or more of the following: Optimization, Programming/Scripting Languages, Statistics, Reinforcement Learning, Causal Inference, Large Language Models, Time Series, Graph Modeling, Supervised/Unsupervised Learning, Deep Learning, Predictive Modeling ...

The Brand Experience (BX) organization creates, builds and leads innovation for Brand Owners in the Amazon store worldwide. Our growing portfolio of BX tools enable Brands to tell their unique Brand and product stories, optimize content through statistical experimentation, solicit and manage reviews to earn Customer trust and grow their business as well as engage with new and loyal Customers through a variety of channels.We are looking for a Applied Scientist to drive data insights and opportunities to improve Brands’ success. As a successful applied scientist on our talented team of scientists and engineers, you will solve complex problems to identify actionable opportunities, and collaborate with engineering, research, and business teams for future innovation. You need to be a sophisticated user and builder of statistical models and put them in production to answer specific business questions. You are an expert at synthesizing and communicating insights and recommendations to audiences of varying levels of technical sophistication. You will continue to contribute to the research community, by working with scientists across Amazon, as well as collaborating with academic researchers and publishing papers (www.aboutamazon.com/research).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 ...

Are you excited about developing generative AI and foundation models to revolutionize automation, robotics and computer vision? Are you looking for opportunities to build and deploy them on real problems at truly vast scale? At Amazon Fulfillment Technologies and Robotics we are on a mission to build high-performance autonomous systems that perceive and act to further improve our world-class customer experience - at Amazon scale. This role is for the AFT AI team which has deep expertise developing cutting edge AI solutions at scale and successfully applying them to business problems in the Amazon Fulfillment Network. These solutions typically utilize machine learning and computer vision techniques, applied to text, sequences of events, images or video from existing or new hardware. The team is comprised of scientists, who develop machine learning and computer vision solutions, analytics, who evaluate the expected business impact for a project and the performance of these solutions, and software engineers, who provide necessary support such as annotation pipelines and machine learning library development.We are looking for an Applied Scientist with expertise in computer vision. You will work alongside other CV scientists, engineers, product managers and various stakeholders to deploy vision models at scale across a diverse set of initiatives. If you are a self-motivated individual with a zeal for customer obsession and ownership, and are passionate about applying computer vision for real world problems - this is the team for you. Key job responsibilities- You will be part of a team of scientists and engineers and will work on scaling systems to production along side partner teams.- You will learn how to build robust solutions that operate at Amazon scale, and work with senior technical leaders to grow your skills.- You will face a high level of research ambiguity and problems that require creative, ambitious, and inventive solutions. - You will design and implement scalable solutions and solve complex problems- You will mentor and coach junior software developers- You should be a great communicator and should be motivated to achieve results in a fast-paced, and at times ambiguous, environment- You should be a self-starter with a bias towards independent problem solving.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 Coverage2. Maternity and Parental Leave Options3. Paid Time Off (PTO)4. 401(k) PlanIf 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 teamAmazon Fulfillment Technologies (AFT) powers Amazon’s global fulfillment network. We invent and deliver software, hardware, and data science solutions that orchestrate processes, robots, machines, and people. We harmonize the physical and virtual world so Amazon customers can get what they want, when they want it.The AFT AI team has deep expertise developing cutting edge AI solutions at scale and successfully applying them to business problems in the Amazon Fulfillment Network. These solutions typically utilize machine learning and computer vision techniques, applied to text, sequences of events, images or video from existing or new hardware. We influence each stage of innovation from inception to deployment, developing a research plan, creating and testing prototype solutions, and shepherding the production versions to launch.Our team is the central machine learning and computer vision team supporting all of AFT. The team is comprised of scientists, who develop machine learning and computer vision solutions, analytics, who evaluate the expected business impact for a project and the performance of these solutions, and software engineers, who provide necessary support such as annotation pipelines and machine learning library development.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 developing and implementing deep learning algorithms, particularly with respect to computer vision algorithms- 1+ years of building models for business application experience ...

Why this job is awesome?This is SUPER high-visibility work: Our mission is to provide consistent, accurate, and relevant delivery information to every single page on every Amazon-owned site.MILLIONS of customers will be impacted by your contributions: The changes we make directly impact the customer experience on every Amazon site. This is a great position for someone who likes to leverage Machine learning technologies to solve the real customer problems, and also wants to see and measure their direct impact on customers.We are a cross-functional team that owns the ENTIRE delivery experience for customers: From the business requirements to the technical systems that allow us to directly affect the on-site experience from a central service, business and technical team members are integrated so everyone is involved through the entire development process.You will have a chance to develop the state-of-art machine learning, including deep learning and reinforcement learning models, to build targeting, recommendation, and optimization services to impact millions of Amazon customers.- Do you want to join an innovative team of scientists and engineers who use machine learning and statistical techniques to deliver the best delivery experience on every Amazon-owned site?- Are you excited by the prospect of analyzing and modeling terabytes of data on the cloud and create state-of-art algorithms to solve real world problems?- Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company?- Do you like to innovate and simplify?If yes, then you may be a great fit to join the DEX AI team.Key job responsibilities- Research and implement machine learning techniques to create scalable and effective models in Delivery Experience (DEX) systems- Solve business problems and identify business opportunities to provide the best delivery experience on all Amazon-owned sites.- Design and develop highly innovative machine learning and deep learning models for big data.- Build state-of-art ranking and recommendations models and apply to Amazon search engine.- Analyze and understand large amounts of Amazon’s historical business data to detect patterns, to analyze trends and to identify correlations and causalities- Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementationBASIC 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 ...

The Artificial General Intelligence (AGI) team is seeking a dedicated, skilled, and innovative Applied Scientist with a robust background in deep learning, to build industry-leading technology with Large Language Models (LLMs) and multimodal systems.Key job responsibilitiesAs part of the AGI team, an Applied Scientist will collaborate closely with talented colleagues to lead the development of advanced approaches and modeling techniques, driving forward the frontier of LLM technology. This includes innovating model-in-the-loop and human-in-the-loop approaches to ensure the collection of high-quality data, safeguarding data privacy and security for LLM training, and more. An Applied Scientist will also have a direct impact on enhancing customer experiences through state-of-the-art products and services that harness the power of speech and language technology. A day in the lifeAn Applied Scientist with the AGI team will support the science solution design, run experiments, research new algorithms, and find new ways of optimizing the customer experience; while setting examples for the team on good science practice and standards. Besides theoretical analysis and innovation, an Applied Scientist will also work closely with talented engineers and scientists to put algorithms and models into practice. The ideal candidate should be passionate about delivering experiences that delight customers and creating robust solutions. They will also create reliable, scalable and high-performance products that require exceptional technical expertise, and a sound understanding of Machine Learning.BASIC QUALIFICATIONS- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- 1+ years of building models for business application experience- Experience programming in Java, C++, Python or related language- Experience with Large Language Models (LLMs) or multimodal architectures ...

Are you seeking an environment where you can drive innovation? Do you want to be at the forefront of applying machine learning to solve real world problems? Do you want to play a key role in the future of Amazon's Stores business? Come and join us!The Supply Chain Optimization Technologies (SCOT) group is seeking a Principal Applied Scientist to join our Reinforcement Learning team. Our research team, which includes Sham Kakade and Dean Foster, has published research in top journals and conferences and has a significant impact on the field. Through the launch of several Deep RL models into production, our work also affects decision making in the real world.Key job responsibilitiesKey job responsibilities include:- Design, implement and evaluate models, agents and software prototypes- Technical leadership for a group of highly motivated and talented scientists- Engage key business stakeholders and scientists to surface opportunities for improvement and identify business requirements. - Work closely with partner teams to develop solutions to ambiguous business problems and integrate novel methodology into our team and business.- Work closely with senior science advisor, collaborate with other scientists and engineers, and be part of Amazon’s vibrant and diverse global science community.- Raise the bar of scientific research by innovating and publishingAbout the teamSupply Chain Optimization Technologies (SCOT) owns Amazon’s global inventory planning systems. We decide what, when, where, and how much we should buy to meet Amazon’s business goals and to make our customers happy. We decide how to place and move inventory within Amazon’s fulfillment network. We do this for hundreds of millions of items and hundreds of product lines worth billions of dollars of world-wide. Venturing beyond traditional operations research methods for sequential decision-making in inventory planning, the Reinforcement Learning team is pioneering the application of reinforcement learning techniques for these applications. The team combines empirical research and real world testing, backed by a robust theoretical foundation. Some research publications include:- Deep Inventory Management [https://arxiv.org/abs/2210.03137, NeurIPS 2022 Workshop Presentation] - Learning an Inventory Control Policy with General Inventory Arrival Dynamics [https://arxiv.org/abs/2310.17168]- Meta-Analysis of Randomized Experiments with Applications to Heavy-Tailed Response Data [https://arxiv.org/abs/2112.07602]- What are the Statistical Limits of Offline RL with Linear Function Approximation? [https://arxiv.org/abs/2010.11895, NeurIPS 2021 Workshop Presentation]- A Study on the Calibration of In-context Learning [https://arxiv.org/abs/2312.04021]We encourage collaboration across teammates and recognizes the need to take chances and try new ideas that may fail. Furthermore, our builder culture means that Scientists and Software Development Engineers work closely together to invent and construct at a massive scale.BASIC QUALIFICATIONS- PhD in one of the following disciplines: Computer Science, Machine Learning, Statistics, Applied Math or a related quantitative field- 10+ years of relevant, broad research experience after PhD- Publications at top-tier peer-reviewed conferences or journals in one of these areas: reinforcement learning, deep learning, and machine learning- Fluency in Python, SQL or similar scripting languages and skilled at Java, C++, or other programing languages.- Strong algorithm development experience- Depth and breadth in state-of-the-art machine learning technologies- Strong prior experience with mentorship and/or management of senior scientists and engineers. ...

We are seeking an Applied Scientist for our Device Ad Products science team. This team addresses challenging optimization problems related to how advertisements are priced, selected, allocated and shown to customers on Amazon devices including Fire TV, Alexa and Fire Tablet. As Applied Scientist, you will be responsible for improving advertising performance and delivering innovative advertising experiences for display and video ads on Amazon Devices. This team leads initiatives to improve advertising fundamentals such as relevance, coverage, CTR, and CPSU (cost per sign up for streaming services) which in turn increase advertising revenue across Amazon's devices worldwide. You will own the scoping, implementation, and launch of science based ad solutions and experiences specifically for these entertainment focused environments. Key job responsibilities- Gain a comprehensive understanding of the customer lifecycle journey with Amazon Ads, and develop sophisticated models to optimize various conversion KPIs for enhanced marketing effectiveness.- Develop scalable data processing pipelines and architectures to ingest, transform, and enrich Customer data from various sources (Retail, Prime Video, FireTV and AppStore).- Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with product managers and engineers to launch your models to customers.- Drive innovation within your team and partner closely with other scientists, engineers and Product Managers to build science roadmaps- Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.- Stay up-to-date with the latest advancements in machine learning, natural language processing, knowledge representation, and related fields, and identify opportunities to apply them to Advertising Use Cases.- Effectively communicate complex science problems and solutions to both technical and non-technical audiences.A day in the lifeIn this role, you will regularly work with scientists and technical leaders across the advertising organization, including other science teams, product management, and senior leadership. You will also collaborate with science leaders across Amazon Devices and Prime Video organizations to build company-wide alignment. You will manage and work closely alongside your team of applied and data scientists to guide them through high-ambiguity problems and deliver robust, scalable solutions. About the teamThis role is on Device Ads and Personalization (DAPP) team, which is under Amazon Publisher Monetization (APM). This team has a vision to create innovative Ad experiences on Amazon Devices, providing customers better convenience and more selection.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 ...

This is a unique opportunity for a postdoc to work on research projects that investigate state of the art NLP, IR, and LLM approaches for understanding retail products and their pricing. This will include working with billion-scale datasets and investigating how the world knowledge captured by LLMs reflects real world prices, and investigating more advanced prompting and reasoning techniques to construct large knowledge graphs that are specialized for various pricing use cases such as probabilistic price estimation, as well as error detection and correction.Key job responsibilitiesIn this role you will:• Work closely with a senior science advisor, collaborate with other scientists and engineers, and be part of Amazon’s vibrant and diverse global science community.• Publish your innovation in top-tier academic venues and hone your presentation skills.• Be inspired by challenges and opportunities to invent cutting-edge techniques in your area(s) of expertise. About the teamThe retail pricing science team is a centralized diverse team of STEM scientists that develop statistical, ML, RL, optimization and economic models that drive pricing for products sold by Amazon worldwide, as well as monitoring of prices and experimentations in pricing. The team has a dual focus on competitiveness and long term financial optimality.BASIC QUALIFICATIONSBasic qualifications include: - PhD in a relevant field, received within 2 years of starting the program- Proven publication record in Operation Research, Management Science, Statistics, Machine Learning, Computer Science, Econ, or other related technical fields- Experience in data science and quantitative research- Proficiency in technologies relevant to the subfield ...

Lead the development of cutting-edge AI models to power Amazon's eCommerce ontology - the authoritative source of product knowledge driving exceptional customer experiences. Applied Scientists in this role solve problems related to product classification, attribute extraction, ontology modeling, data integration and enrichment, and scalable knowledge services. It's challenging due to the vast scale, heterogeneous data sources, and evolving domains, but exciting for pushing boundaries in ML, NLP, and knowledge representation research.If you're passionate about driving innovation at scale, we want to hear from you!Key job responsibilities- Lead the research and development of novel AI solutions to enrich and curate Amazon's product ontology (Product Knowledge) at scale- Develop scalable data processing pipelines and architectures to ingest, transform, and enrich product data from various sources (seller listings, customer reviews, etc.)- Collaborate with engineers to design and implement robust services- Work closely with product managers, stakeholders, and subject matter experts to identify opportunities for innovation and drive the roadmap for Product Knowledge- Mentor and upskill junior scientists and engineers, fostering a culture of continuous learning and knowledge sharing- Communicate complex technical concepts and research findings effectively to diverse audiences, including leadership, cross-functional teams, and the wider scientific community- Stay up-to-date with the latest advancements in machine learning, natural language processing, knowledge representation, and related fields, and identify opportunities to apply them to Product KnowledgeA day in the lifeThe Amazon product ontology is a structured knowledge base representing product types, attributes, classes, and relationships. It standardizes product data, enabling enhanced customer experiences through improved search and recommendations, streamlined selling processes, and internal data enrichment across Amazon's eCommerce ecosystem.You will work with following stakeholders:- Product Managers represent customer experiences and selling partner experiences- Category Leaders (e.g., apparel, electronics) provide domain knowledge and guidance as subject matter experts- Engineers build and maintain data pipelines and services in production- Ontologists design data models and define guidelines - Other Applied Scientists collaborate on research and innovationAbout the teamThe Product Knowledge team at Amazon is dedicated to creating the industry-standard eCommerce product and services ontology. Our diverse team of applied scientists, engineers, ontologists and subject matter experts build a comprehensive ontology enabling exceptional customer and selling partner experiences through high-quality, contextual product knowledge at scale.BASIC QUALIFICATIONS- 4+ years of applied research experience- 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 ...

Exciting opportunity to design, build and deploy the next generation of attribution models to provide advertisers with actionable information that will allow them to optimally allocate advertising dollars. 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- Knowledge of programming languages such as C/C++, Python, Java or Perl- Experience programming in Java, C++, Python or related language- Experience with neural deep learning methods and machine learning ...

As part of the AWS Solutions organization, we have a vision to provide business applications, leveraging Amazon’s unique experience and expertise, that are used by millions of companies worldwide to manage day-to-day operations. We will accomplish this by accelerating our customers’ businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. We blend vision with curiosity and Amazon’s real-world experience to build opinionated, turnkey solutions. Where customers prefer to buy over build, we become their trusted partner with solutions that are no-brainers to buy and easy to use.AWS Industry Products (IP) is a new AWS engineering organization chartered to build new AWS products by applying Amazon’s innovation mechanisms along with AWS digital technologies to transform the world, industry by industry. We dive deep with leaders and innovators to solve the problems which block their industries, enabling them to capitalize on new digital business models. Simply put, our goal is to use the skill and scale of AWS to make the benefits of a connected world achievable for all businesses. We are looking for Research Scientists who are passionate about transforming industries through AI. This is a unique opportunity to not only listen to industry customers but also to develop AI and generative AI expertise in multiple core industries. You will join a team of scientists, product managers and software engineers that builds AI solutions in automotive, manufacturing, healthcare, sustainability/clean energy, and supply chain/operations domains. Leveraging and advancing generative AI technology will be a big part of your charter as we seek to apply the latest advancements in generative AI to industry-specific problemsUsing your in-depth expertise in machine learning and generative AI, you will take the lead on tactical and strategic initiatives to deliver reusable science components and services that differentiate our industry products and solve customer problems. You will be the voice of scientific rigor, delivery, and innovation as you work with our segment teams on AI-driven product differentiators. You will conduct and advance research in AI and generative AI within and outside Amazon.Extensive knowledge of both state-of-the-art and emerging AI methods and technologies is expected. Hands-on knowledge of generative AI, foundation models and commitment to learn and grow in this field are expected. Basic qualificationsPhD, or Master's degree and 10+ years of quantitative field research experienceExperience investigating the feasibility of applying scientific principles and concepts to business problems and productsExperience analyzing both experimental and observational data setsPreferred qualificationsKnowledge of R, MATLAB, Python or similar scripting languageAbout the teamWhy 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.Diverse ExperiencesAWS values diverse experiences. Even if you do not meet all of the 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.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.Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. BASIC QUALIFICATIONS- 10+ years of tech industry or equivalent experience- PhD in a quantitative discipline such as statistics, mathematics, economics, computer science, or any related quantitative field- Experience working effectively with science, data processing, and software engineering teams ...

Amazon is investing heavily in building a world class advertising business and developing a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses for 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. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities.We are seeking a technical leader for our Supply Science team. This team is within the Sponsored Product team, and works on complex engineering, optimization, econometric, and user-experience problems in order to deliver relevant product ads on Amazon search and detail pages world-wide. The team operates with the dual objective of enhancing the experience of Amazon shoppers and enabling the monetization of our online and mobile page properties. Our work spans ML and Data science across predictive modeling, reinforcement learning (Bandits), adaptive experimentation, causal inference, data engineering.Key job responsibilitiesSearch Supply and Experiences, within Sponsored Products, is seeking an Applied Scientist to join a fast growing team with the mandate of creating new ads experience that elevates the shopping experience for our hundreds of millions customers worldwide. We are looking for a top analytical mind capable of understanding our complex ecosystem of advertisers participating in a pay-per-click model– and leveraging this knowledge to help turn the flywheel of the business.As an Applied Scientist on this team you will:--Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production.--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.--Work closely with software engineers to assist in productionizing your ML models.--Research new machine learning approaches.A day in the lifeThe successful candidate will be a self-starter comfortable with ambiguity, with strong attention to detail, and with an ability to work in a fast-paced, high-energy and ever-changing environment. The drive and capability to shape the direction is a must.About the teamWe are a customer-obsessed team of engineers, technologists, product leaders, and scientists. We are focused on continuous exploration of contexts and creatives where advertising delivers value to customers and advertisers. We specifically work on new ads experiences globally with the goal of helping shoppers make the most informed purchase decision. We obsess about our customers and we are continuously innovating on their behalf to enrich their shopping experience on AmazonBASIC 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'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 ...

AWS AI is looking for passionate, talented, and inventive Applied Scientists with a strong machine learning background to help build industry-leading Conversational AI Systems. Our mission is to provide a delightful experience to Amazon’s customers by pushing the envelope in Natural Language Understanding (NLU), Dialog Systems including Generative AI with Large Language Models (LLMs) and Applied Machine Learning (ML).As part of our AI team in Amazon AWS, you will work alongside internationally recognized experts to develop novel algorithms and modeling techniques to advance the state-of-the-art in human language technology. Your work will directly impact millions of our customers in the form of products and services that make use language technology. You will gain hands on experience with Amazon’s heterogeneous text, structured data sources, and large-scale computing resources to accelerate advances in language understanding.We are hiring in all areas of human language technology: NLU, Dialog Management, Conversational AI, LLMs and Generative AI.A day in the lifeThe Amazon Web Services (AWS) Next Gen DevX (NGDE) team uses generative AI and foundation models to reimagine the experience of all builders on AWS. From the IDE to web-based tools and services, AI will help engineers work on large and small applications. We explore new technologies and find creative solutions. Curiosity and an explorative mindset can find a place here to impact the life of engineers around the world.If you are excited about this space and want to enlighten your peers with new capabilities, this is the team for you.We are open to hiring candidates to work out of one of the following locations:Santa Clara, CA, USAAbout the teamAWS 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.Diverse ExperiencesAWS values diverse experiences. Even if you do not meet all of the 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. BASIC QUALIFICATIONS- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- 3+ years of building models for business application 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 ...

Are you excited about developing algorithms and models to power Amazon's next generation robotic storage systems? Are you looking for opportunities to build and deploy them on real problems at truly vast scale? At Amazon Fulfillment Technologies and Robotics we are on a mission to build high-performance autonomous systems that perceive and act to further improve our world-class customer experience - at Amazon scale. We are looking for enthusiastic scientists for a variety of roles.The Research team at Amazon Robotics is seeking a passionate, collaborative, hands-on Research Scientist to develop planning and scheduling algorithms to support Amazon's next generation robotic storage systems. The focus of this position workflow optimization and robot task-assignment. It includes designing and evaluating planning and scheduling algorithms using a combination of machine learning and optimization methods as appropriate. This work spans from research such optimal decision making, to policy learning, to experimenting using simulation and modeling tools, to running large-scale A/B tests on robots in our facilities.The ideal candidate for this position will be familiar with planning or learning algorithms at both the theoretical and implementation levels. You will have the chance to solve complex scientific problems and see your solutions come to life in Amazon’s warehouses!Key job responsibilities- Research design - How should solve a particular research problem- Research delivery - Proving/dis-proving strategies in offline data or in simulation- Production studies - Insights from production data or ad-hoc experimentation- Prototype implementation - Building key parts of algorithms or model prototypesA day in the lifeOn a typical day in this role you will work to progress your research projects, meet with engineering, systems, and solutions stakeholders, brainstorm with other scientists on the team, and participate in team processes. You will follow your research projects though the entire life cycle of design, implementation, evaluation, analysis, and will communicate your findings and results through technical papers and reports. You will consult with engineering teams as they incorporate your models and analyses into system and process designs.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) PlanIf 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 teamOur multi-disciplinary science team includes scientists with backgrounds in simulation, planning and scheduling, grasping and manipulation, machine learning, and operations research. We develop novel planning algorithms and machine learning methods and apply them to real-word robotic warehouses, including:* Planning and coordinating the paths of thousands of robots* Dynamic allocation and scheduling of tasks to thousands of robots* Learning how to adapt system behavior to varying operating conditions* Co-design of robotic logistics processes and the algorithms to optimize themOur team also serves as a hub to foster innovation and support scientists across Amazon Robotics. We also coordinate research engagements with academia, such as the Robotics section of the Amazon Research Awards.BASIC QUALIFICATIONS- PhD, or Master's degree and 4+ years of quantitative field research experience- Experience investigating the feasibility of applying scientific principles and concepts to business problems and products- Experience analyzing both experimental and observational data sets- Knowledge of R, MATLAB, Python or similar scripting language- Experience in planning and optimization ...

Amazon Web Services is looking for world class scientists to join the Security Analytics and AI Research team within AWS Security Services. This group is entrusted with researching and developing core data mining and machine learning algorithms for various AWS security services like GuardDuty (https://aws.amazon.com/guardduty/). In this group, you will invent and implement innovative solutions for never-before-solved problems. If you have passion for security and experience with large scale machine learning problems, this will be an exciting opportunity.The AWS Security Services team builds technologies that help customers strengthen their security posture and better meet security requirements in the AWS Cloud. The team interacts with security researchers to codify our own learnings and best practices and make them available for customers. We are building massively scalable and globally distributed security systems to power next generation services.Key job responsibilities* Invent, implement, and deploy state of the art machine learning and deep learning models and systems for information security applications.* Rapidly design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both quantitative and business judgment.* Collaborate with software engineering teams to integrate successful experiments into large scale, highly complex production services.* Report results in a scientifically rigorous way.* Interact with security engineers, product managers and related domain experts to dive deep into the types of challenges that we need innovative solutions for.About the teamWhy 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.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.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 field experience in Computer Science, Machine Learning, Operational Research, Statistics or a related quantitative field.- Working knowledge of natural language processing (NLP) or large language model (LLM).- Experience with unsupervised learning, semi-supervised learning and continual learning.- Hands-on experience in predictive modeling and analysis.- Algorithm development experience.- Proficient in coding with at least one of the following: Java, C++, Python, Scala, Rust or other programming language.- Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning. ...

Do you want to join an innovative team of scientists who invent and apply the most advanced machine learning and NLP techniques to create the best customer engagement experience on the earth? Do you want to revolutionize the way how customers solve their issues and get their questions answered? At Customer Engagement Technology (CET), we develop peculiar products that help customers solve problems. We innovate on behalf of customers, developing Bot, self-service, and associate-facing products that delight customers and support our world class customer service workforce. We are looking for talented Postdoctoral Scientists to join our CET Machine Learning team in Seattle, WA for a one-year, full-time research position to work on research and development of task oriented dialogue agents for the customer support domain. We utilize Large Language Models (LLMs) to address challenges within TOD systems, such as Natural Language Generation for generating system responses based, state tracking, decision making etc. We publish our research in top tier NLP and AI venues (EMNLP, ACL, AAAI, etc), and deploy ML powered chatbots primarily in the customer returns domain. Key job responsibilitiesIn this role you will: • Work closely with a senior science advisor, collaborate with other scientists and engineers, and be part of Amazon’s vibrant and diverse global science community. • Publish your innovation in top-tier academic venues and hone your presentation skills. • Be inspired by challenges and opportunities to invent cutting-edge techniques in your area(s) of expertise.BASIC QUALIFICATIONS• PhD in a relevant field, received within 2 years of starting the program • Proven publication record in Machine Learning, Computer Vision, AI, Computer Science, or other related technical fields • Experience in data science and quantitative research • Proficiency in technologies relevant to the subfield• Experience in Natural Language Processing, and in particular Large Language Models ...

At OpsTech Solutions (OTS), we are a technology centric services organization that designs, builds, and sustains the invisible, high-quality network, compute infrastructure and device scaffolding that empowers and protects Amazon’s global Operations. The OTS DataTech team drives enterprise data strategy and support across OTS. Our charter encompasses OTS-wide efforts, including Data as a Product (DaaP), enterprise data infrastructure, AI/ML capability, and supporting specific business-critical programs, fueling innovation and automation for OTS.We are looking for a passionate, talented, and innovative Applied Scientist with a background in developing and implementing state-of-the-art machine learning solutions within the realms of supervised and unsupervised learning, Generative AI (GenAI), and optimization. Key job responsibilitiesIn this role, you will play a pivotal role in shaping the vision, roadmap, design, development, and implementation of science based solutions from beginning to end. - You will contribute to building and maintaining an MLOps Platform that will support end-to-end scientific operations for a wide range of AI/ML use cases. You will be responsible for the seamless integration of scientific products with existing systems, ultimately leading to increased operational efficiency and productivity across OTS. - You will also have the opportunity to leverage our foundational GenAI platform to help OTS customers build GenAI applications for their use cases.- You will be closely partnering with a cross-functional team of stakeholders including with Applied Scientists, Data Scientists, Machine Learning Engineers, Data Engineers, Product Managers, and Technical Program Managers.Come join OTS DataTech as we continue to innovate and pioneer the AI/ML space within OTS!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: - Medical, Dental, and Vision Coverage - Maternity and Parental Leave Options - Paid Time Off (PTO) - 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!BASIC QUALIFICATIONS- MS or PhD in quantitative field (CS, CE, ML preferred) or equivalent relevant work Strong background in machine learning, including supervised and unsupervised learning algorithms.- Experience developing, building and implementing complex software systems, especially involving ML, that have been successfully delivered to customers.- Knowledge of Generative AI and its applications.- Proficiency in programming languages such as Python, Java, or C++.- Strong communication skills, both written and verbal. ...

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses. Amazon's advertising portfolio helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers. 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! As an Applied Scientist on this team, you will: - Be a strong contributor to Machine Learning; lending effort within this team and across other teams.- Perform hands-on analysis and modeling of enormous data sets to develop insights that increase traffic monetization and 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.Why you will love this opportunity: Amazon is investing heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate.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.Team video https://youtu.be/zD_6Lzw8raE 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 ...