Machine Learning Science

Are you excited by the idea of developing personalized experiences for Amazon customers as they shop? Are you looking for new challenges and to solve hard science problems while applying state-of-the-art recommendation system modeling techniques? Join us and you'll help millions of customers make informed purchase decisions while also advancing the state of Amazon's science by publishing research!Key job responsibilities- Participate in the design, development, evaluation, deployment and updating of data-driven models for shopping personalization.- Use expertise in supervised and uplift learning algorithms to improve ML performance- Research and implement novel ML and statistical approaches to add value to the business.- Design A/B tests and conduct statistical analysis on their results- Work with distributed machine learning and statistical algorithms to harness enormous volumes of data at scale to serve our customers- Work closely with internal stakeholders like the business teams, engineering teams and partner teams and align them with respect to your focus area- Present and publish science research, contributing to Amazon's science community- Mentor junior engineers and scientists.About the teamOur team's mission is to surface the right payments-related recommendations to customers at the right time, helping create a rewarding and successful shopping experience for Amazon's customers. Our team's culture is highly collaborative, with an emphasis on supporting each other and learning from one another. We dedicate time each week to focus on personal development and expanding our knowledge as a team. We also highly value having a big impact, both for Amazon's business and for our customers.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- Experience with reinforcement learning- Publication record on machine learning methods ...

Do you want to join an innovative team of scientists who use machine learning and statistical techniques to help Amazon provide the best customer experience by preventing eCommerce fraud?Are you excited by the prospect of analyzing and modeling terabytes of data and creating state-of-the-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 enjoy collaborating in a diverse team environment?If yes, then you may be a great fit to join the Amazon Buyer Risk Prevention (BRP) Machine Learning group. We are looking for a talented scientist who is passionate to build advanced algorithmic systems that help manage safety of millions of transactions every day.Key job responsibilitiesUse machine learning and statistical techniques to create scalable risk management systemsLearning and understanding large amounts of Amazon’s historical business data for specific instances of risk or broader risk trendsDesign, development and evaluation of highly innovative models for risk managementWorking closely with software engineering teams to drive real-time model implementations and new feature creationsWorking closely with operations staff to optimize risk management operations,Establishing scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementationTracking general business activity and providing clear, compelling management reporting on a regular basisResearch and implement novel machine learning and statistical approachesBASIC QUALIFICATIONS- Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field- Experience programming in Java, C++, Python or related language- Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse ...

Conversational AI ModEling and Learning (CAMEL) team is part of Amazon Devices organization where our mission is to build a best-in-class Conversational AI that is intuitive, intelligent, and responsive, by developing superior Large Language Models (LLM) solutions and services which increase the capabilities built into the model and which enable utilizing thousands of APIs and external knowledge sources to provide the best experience for each request across millions of customers and endpoints. We are looking for a passionate, talented, and resourceful Applied Scientist in the field of LLM, Artificial Intelligence (AI), Natural Language Processing (NLP), Recommender Systems and/or Information Retrieval, to invent and build scalable solutions for a state-of-the-art context-aware conversational AI. A successful candidate will have strong machine learning background and a desire to push the envelope in one or more of the above areas. The ideal candidate would also have hands-on experiences in building Generative AI solutions with LLMs, enjoy operating in dynamic environments, be self-motivated to take on challenging problems to deliver big customer impact, moving fast to ship solutions and then iterating on user feedback and interactions.Key job responsibilitiesAs an Applied Scientist, you will leverage your technical expertise and experience to collaborate with other talented applied scientists and engineers to research and develop novel algorithms and modeling techniques to reduce friction and enable natural and contextual conversations. You will analyze, understand and improve user experiences by leveraging Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in artificial intelligence. You will work on core LLM technologies, including Prompt Engineering and Optimization, Supervised Fine-Tuning, Learning from Human Feedback, Evaluation, Self-Learning, etc. Your work will directly impact our customers in the form of novel products and services.BASIC QUALIFICATIONS- PhD, or Master's degree and 2+ years of building machine learning models for business application experience- PhD, or a Master's degree and experience in CS, CE, ML or related field research- Experience programming in Java, C++, Python or related language- 3+ years’ experience with modeling languages and tools like PyTorch / TensorFlow, R, scikit-learn, numpy, scipy, etc- Solid ML background and familiar with standard NLU, NLG, and LLM techniques ...

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 ...

Do you want to join an innovative team of scientists who use deep learning, natural language processing, large language models to help Amazon provide the best seller experience across the entire Seller life cycle, including recruitment, growth, support and provide the best customer and seller experience by automatically mitigating risk?Do you want to build advanced algorithmic systems that help manage the trust and safety of millions of customer interactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data and creating state-of-the-art algorithms to solve real world problems? Are you excited by the opportunity to leverage GenAI and innovate on top of the state-of-the-art large language models to improve customer and seller experience? Do you like to build end-to-end business solutions and directly impact the profitability of the company? Do you like to innovate and simplify processes?If yes, then you may be a great fit to join the Machine Learning Accelerator team in the Amazon Selling Partner Services (SPS) group.Key job responsibilitiesThe scope of an Applied Scientist II in the SPS Machine Learning Accelerator (MLA) team is to research and prototype Machine Learning applications that solve strategic business problems across SPS domains. Additionally, the scientist collaborates with project leaders, engineers and business partners to design and implement solutions at scale. The scientist focuses on components of large-scale projects, systems and products and can work independently and with the team to deliver successful solutions with medium to large business impact. The scientist helps our team evolve by actively participating in discussions, team planning, and by staying current on the latest techniques arising from both the scientist community in SPS, the larger Amazon-wide community, and beyond. The scientist develops and introduces tools and practices that streamline the work of the team, and he mentors junior team members and participates in hiring.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 are reimagining Amazon Search by introducing an interactive conversational experience that makes finding the perfect product easier than ever. With our state-of-the-art Large Language Model (LLM) innovations, you can now ask product-related questions, compare products, receive personalized suggestions, and more—all through a fast and reliable natural language conversation. This is just the beginning of a new era in online shopping, and the future is yours to shape.We're searching for pioneers who are passionate about technology, innovation, and customer experience, and who are ready to make a lasting impact on the industry. You'll be working with talented scientists, and engineers 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 and change the world of eCommerce forever!BASIC QUALIFICATIONS- 3+ years of scientists or machine learning engineers management experience- Knowledge of ML, NLP, Information Retrieval and Analytics- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field ...

Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply cutting edge Generative AI algorithms to solve real world problems with significant impact? Amazon Web Services (AWS) Professional Services (ProServe) is looking for Machine Learning Engineers who like helping U.S. Federal agencies implement innovative cloud computing solutions and solve technical problems using state-of-the-art language models in the cloud. AWS ProServe engages in a wide variety of projects for customers and partners, providing collective experience from across the AWS customer base and are obsessed about strong success for the Customer. Our team collaborates across the entire AWS organization to bring access to product and service teams, to get the right solution delivered and drive feature innovation based upon customer needs.At AWS, we're hiring experienced Machine Learning Engineers with a background in NLP, generative AI, and document processing to help our customers understand, plan, and implement best practices around leveraging these technologies within their AWS cloud environments. Our consultants deliver proof-of-concept projects, reusable artifacts, reference architectures, and lead implementation projects to assist organizations in harnessing the power of their data and unlocking the potential of advanced NLP and AI capabilities.In this role, you will work closely with national security customers to deeply understand their data challenges and requirements, and design tailored solutions that best fit their use cases. You should have deep expertise in NLP/NLU, generative AI, and building data-intensive applications at scale. You should possess excellent business acumen and communication skills to collaborate effectively with stakeholders, develop key business questions, and translate requirements into actionable solutions. You will provide guidance and support to other engineers, sharing industry best practices and driving innovation in the field of data science and AI.It is expected to work from one of the above locations (or customer sites) at least 1+ days in a week. This is not a remote position. You are expected to be in the office or with customers as needed.This position requires that the candidate selected must currently possess and maintain an active TS/SCI Security Clearance with Polygraph. The position further requires the candidate to opt into a commensurate clearance for each government agency for which they perform AWS work.Key job responsibilitiesAs a Machine Learning Engineer, you are proficient in developing and deploying advanced ML models to solve diverse challenges and opportunities. You will be working alongside scientists to develop novel models to solve real-world problems. You'll design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. You will apply classical ML algorithms and cutting-edge deep learning (DL) approaches to areas within the natural language processing and understanding spaces including GenAI, document processing and understanding, call center analytics, and chat experiences.The primary responsibilities of this role are to:- Interact with customer directly to understand their business problems, and help them with defining and implementing scalable ML/DL solutions to solve them- Work closely with account teams, research scientist teams, and product engineering teams to drive model implementations and new algorithmsAbout 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.Work/Life BalanceWe value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.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.BASIC QUALIFICATIONS- 3+ years of non-internship professional software development experience- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience- Experience programming with at least one software programming language- 2+ years of relevant experience in developing and deploying large scale machine learning or deep learning models and/or systems into production, including batch and real-time data processing, model containerization, CI/CD pipelines, API development, model training and productionizing ML models- Current, active US Government Security Clearance of TS/SCI with Polygraph ...

Amazon is investing heavily in building a world class advertising business and we are responsible for 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. 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.The Sponsored Brands Advertiser Control team is a versatile environment, with a wide variety of challenges. We guide advertisers to make informed decisions by sharing insights and forecasts. We help advertisers deliver effective campaigns automatically by optimizing bids and targets on behalf of them. We enable advertisers to achieve brand advertising goals with maximum efficiency. We look at mega size data from both retail and advertising space, and coming up with ML and DL based science solutions through multiple products. In this role you will: - Research and build innovative machine learning and deep learning models utilizing the latest technologies such as LLM to provide personalized targeting, real-time forecasting and simplify campaign creation and management- Develop optimization solutions to automate bidding , targeting and budgeting on behalf of advertisers - Perform hands-on big data analysis and modeling to develop insights that increase advertiser monetization and merchandise sales without compromising shopper experience. - Design and run A/B experiments that affect hundreds of millions of customers, evaluate the impact of your optimizations and communicate your results to various business stakeholders. - Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving. - Write production code to bring models into production. - Work closely with software engineers on detailed requirements, technical designs and implementation of end-to-end solutions in production. - Work with scientists and economists to model the interaction between organic sales and sponsored content and to further evolve Amazon's marketplace.Why you love this opportunity Amazon is investing heavily in building a world-class advertising business. This team is responsible for defining and delivering a collection of self-service performance 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 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 fundamentally 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. 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. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us BASIC QUALIFICATIONS- PhD, or Master's degree and 5+ years of CS, CE, ML or related field experience- 5+ years of building models for business application experience- Experience programming in Java, C++, Python or related language ...

About Amazon Advertising:Amazon Advertising operates at the intersection of eCommerce and advertising, offering a rich array of digital display advertising solutions with the goal of helping our customers find and discover anything they want to buy. We help advertisers of all types to reach Amazon customers on Amazon.com, across our other owned and operated sites, on other high quality sites across the web, and on millions of mobile devices. We start with the customer and work backwards in everything we do, including advertising. If you’re interested in joining a rapidly growing team working to build a unique, world-class advertising group with a relentless focus on the customer, you’ve come to the right place.About our team:Our team, CreativeX optimizations, is responsible for tailoring the visual experience of ads to each context in real time. To accomplish this, we are investing in latent-diffusion models, large language models (LLM), reinforced learning (RL), Computer Vision, and related methods.Key job responsibilitiesWe are looking for talented Applied Scientists who are adept at a variety of skills, especially with reinforcement learning and recommendations, and familiarity with LLMs, latent diffusion, or related foundational models that will accelerate our plans to dynamically optimize ad creatives on behalf of advertisers. Every member of the team is expected to build customer (advertiser) facing features, contribute to the collaborative spirit within the team, publish, patent, and bring cutting edge research to raise the bar within the team.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 ...

Are you a scientist interested in pushing the state of the art in Generative AI, LLMs, LMMs? Are you interested in working on ground-breaking research projects that will lead to great products and scientific publications? Do you wish you had access to large datasets? Answer yes to any of these questions and you’ll fit right in here at Amazon.We are looking for a hands-on researcher, who wants to derive, implement, and test the next generation of Generative AI algorithms in multiple projects ranging from Computer Vision, ML, and NLP. The research we do is innovative, multidisciplinary, and far-reaching. We aim to define, deploy, and publish cutting edge research. In order to achieve our vision, we think big and tackle technology problems that are cutting edge. Where technology does not exist, we will build it. Where it exists we will need to modify it to make it work at Amazon scale. We need members who are passionate and willing to learn. Key job responsibilities- Derive novel computer vision, machine learning, and NLP algorithms.- Define scalable computer vision, machine learning and NLP models.- Invent the next generation of Generative AI models.- Work with large datasets.- Work with software engineering teams to deploy your - Publish your work at top conferences/journals.- Mentor team members.A day in the lifeWe are a team of seasoned scientists. We work on science problems and publish our results at major scientific conferences. We work with multiple other science teams at Amazon.About the teamWe are a tight-knit group that shares our experiences and help each other succeed. We believe in team work. We love hard problems and like to move fast in a growing and changing environment. We use data to guide our decisions and we always push the technology and process boundaries of what is feasible on behalf of our customers. If that sounds like an environment you like, join us.We are open to hiring candidates to work out of one of the following locations:Seattle, WA, USABASIC QUALIFICATIONS- A PhD in CS, ECE, Statistics or in a related, highly quantitative field.- Extensive research expertise in generative AI, computer vision, machine learning, or NLP.- 10+ years of hands-on experience in computer vision, machine learning, or NLP.- Proven record of developing new approaches, algorithms, application areas, etc.- Excellent communication skills.- Excellent skills in problem solving, programming, and computer science fundamentals.- Solid background in statistics, math, CS, machine learning, and computer vision or NLP. ...

Brand Stores (such as www.amazon.com/lego) are a core product offering in the Amazon Advertising portfolio. The brand’s store is their dedicated place on Amazon to differentiate, grow sales, and build loyalty with millions of shoppers. Our mission is to empower brands of all sizes to tell their story in their own unique voice to consumers. We help brands create engaging shopping experiences that assist shoppers in discovering and evaluating them as part of purchase decisions. We succeed when we are both useful to shoppers and when brands can attract and retain shopper’s attention using our products. A cool case study on brand stores can be found here: https://advertising.amazon.com/library/case-studies/nespresso-brand-store-increases-shopper-engagement.We are looking for an Applied Scientist to lead the generation of data driven insights that bring long term value to brands, as well as the idealization and creation of ranking models for brand content. In this role you will influence our team’s science and business strategy with your analyses. You will be expected to identify and solve ambiguous problems and science deficiencies, and to provide informed solutions based on state of the art machine learning research.Why you will love this opportunity: Amazon is investing heavily in building a world-class advertising business. This team collaborate closely with other 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 #adpt-brand-shopping-experiences-scienceKey job responsibilitiesAs an Applied Scientist on this team, you will: - Be the technical leader in Machine Learning; lead efforts 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.About the teamThe Brand Shopping Experience Team (BSX) develops and deploys into production Machine Learning Algorithms that quantify relevance, select and organize Brands’ pieces of content in different placements in Amazon.com. BSX's goal is to create engaging and enjoyable shopping experiences that incentivize Brand discovery and that foster Brand-Customer relationships.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 ...

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 ...

AWS Marketplace is looking for world class scientists to join its AWS Marketplace (MP) in its journey to evolve AI based customer experiences. This group is entrusted with developing core natural language processing, generative AI, deep learning and machine learning algorithms for AWS, with a focus on code development, broadly defined. You will invent, implement, and deploy state of the art machine learning algorithms and systems. You will build prototypes and explore conceptually new solutions. You will interact closely with our customers and with the academic community. As a senior Applied Scientist, you are recognized for your expertise, advise team members on a range of machine learning topics, and work closely with software engineers to drive the delivery of end-to-end modeling solutions. Your work focuses on ambiguous problem areas where the business problem or opportunity may not yet be defined. The problems that you take on require scientific breakthroughs.You take a long-term view of the business objectives, product roadmaps, technologies, and how they should evolve. You drive mindful discussions with customers, engineers, and scientist peers. You bring perspective and provide context for current technology choices, and make recommendations on the right modeling and component design approach to achieve the desired customer experience and business outcome.About the teamDiverse 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. Hybrid WorkWe value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our US Amazon offices.BASIC QUALIFICATIONS- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field- 3+ years of building machine learning models for business application experience- Experience programming in Java, C++, Python or related language ...

The Customer Engagement Technology team leads AI/LLM-driven customer experience transformation using task-oriented dialogue systems. We develop multi-modal, multi-turn, goal-oriented dialog systems that can handle customer issues at Amazon scale across multiple languages. These systems are designed to adapt to changing company policies and invoke correct APIs to automate solutions to customer problems. Additionally, we enhance associate productivity through response/action recommendation, summarization to capture conversation context succinctly, retrieving precise information from documents to provide useful information to the agent, and machine translation to facilitate smoother conversations when the customer and agent speak different languages.Key focus areas include:1. Task-Oriented Dialog Systems: Building reliable, scalable, and adaptive LLM-based agents for understanding intents, determining eligibilities, making API calls, confirming outcomes, and exploring alternatives across hundreds of customer service intents, while adapting to changing policies.2. Lifelong Learning: Researching continuous learning approaches for injecting new domain knowledge while retaining the model's foundational abilities and prevent catastrophic forgetting.3. Agentic Systems: Developing a modular agentic framework to handle multi domain conversations through appropriate system abstractions.4. Complex Multi-turn Instruction Following: Identifying approaches to guarantee compliance with instructions that specify standard operating procedures for handling multi-turn complex scenarios.5. Inference-Time Adaptability: Researching inference-time scaling methods and improving in-context learning abilities of custom models to enable real-time adaptability to new features, actions, or bug fixes without solely relying on retraining.6. Context Adherence: Exploring methods to ground responses in specific customer attributes, account information, and behavioral data to prevent hallucinations and ensure high-fidelity responses.7. Policy Grounding: Investigating techniques to align bot behavior with evolving company policies by grounding on complex, unstructured policy documents, ensuring consistent and compliant actions.1. End to End Dialog Policy Optimization: Researching alignment approaches to optimize successful dialog completions.2. Scalable Evaluations: Developing automated approaches to evaluate quality of experience, and correctness of agentic resolutionsKey job responsibilities1. Research and development of LLM-based chatbots and conversational AI systems for customer service applications.2. Design and implement state-of-the-art NLP and ML models for tasks such as language understanding, dialogue management, and response generation.3. Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to integrate LLM-based solutions into Amazon's customer service platforms.4. Develop and implement strategies for data collection, annotation, and model training to ensure high-quality and robust performance of the chatbots.5. Conduct experiments and evaluations to measure the performance of the developed models and systems, and identify areas for improvement.6. Stay up-to-date with the latest advancements in NLP, LLMs, and conversational AI, and explore opportunities to incorporate new techniques and technologies into Amazon's customer service solutions.7. Collaborate with internal and external research communities, participate in conferences and publications, and contribute to the advancement of the field.A day in the lifeWe thrive on solving challenging problems to innovate for our customers. By pushing the boundaries of technology, we create unparalleled experiences that enable us to rapidly adapt in a dynamic environment. Our decisions are guided by data, and we collaborate with engineering, science, and product teams to foster an innovative learning environment.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!Benefits Summary: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 Coverage2. Maternity and Parental Leave Options3. Paid Time Off (PTO)4. 401(k) PlanAbout the teamJoin our team of scientists and engineers who develop and deploy LLM-based Conversational AI systems to enhance Amazon's customer service experience and effectiveness. We work on innovative solutions that help customers solve their issues and get their questions answered efficiently, and associate-facing products that support our customer service associate workforce.BASIC QUALIFICATIONS- Master's degree- 2+ years of building machine learning models or developing algorithms for business application experience ...

Amazon Search creates powerful, customer-focused product search solutions and technologies. Whenever a customer visits an Amazon site worldwide and types in a query or browses through product categories, our systems go to work. We delight customers when we accurately understand their intent expressed via a query or image, and reflect that understanding throughout the search page - from layout to the search results and navigation. We make shopping effortless by helping customers easily explore our vast selection, narrowing down a myriad of options to a manageable consideration set while providing key information to make high confidence decisions with low post-purchase regretSearch Science Data Infrastructure team is responsible for delivering high quality and fresh ML model training data, and providing seamless access to all ML artifacts through federated Feature Store infrastructure. This big-data platform provides the ML training data to Amazon search ranking, matching quality, search economics and also powers live-site features, including search suggestions, query understanding, spelling, search result ranking, and personalization. Furthermore, 350+ teams across Amazon consume our datasets to power analytics and behavior models. We are located in downtown Palo Alto, a short walk from numerous shops and restaurants, and right across from the Caltrain station.Key job responsibilitiesAs an ML Engineer you will:- Lead development of services and infrastructure at the intersection of machine learning, big data, and distributed systems. Our products and services empower hundreds of science teams across Amazon to deliver machine learning at scale for ML model training, Feature engineering and Data quality monitoring. - You will help manage machine learning lifecycle and operations using AWS AI services, DL compute resources, and our core search backend services for query understanding, semantic matching, and relevance ranking. - You will build scalable data-intensive infrastructure that processes huge amounts of logs, catalogs, transactional data, and telemetry signals. By doing so, we enable teams to become more data-driven and build robust and explainable ML services. - You will work with partners on data experimentation to advance Amazon product search, making it available across all geographic regions with variety of product search and discovery use cases across many categories.- Lead the design, get your hands dirty and write code, and ultimately deploy big data and machine learning services. These services define the foundation of our search R&D processes, supporting science, product development and production of the world’s largest product search engine.- Possess expert knowledge in performance, large scale distributed system scalability, system architecture, and engineering best practices.- Obsess over operational excellence, evaluate system performance, security, design system metrics and driving quality improvementsBASIC QUALIFICATIONS- 3+ years of non-internship professional software development experience- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience- Experience programming with at least one software programming language- Experience in machine learning, data mining, information retrieval, statistics or natural language processing ...

This Principal Applied Scientist will be the science leader across a suite of causal impact models used across Amazon's business. This scientist will oversee development of a scalable framework to calculate incremental impact of Selling Partner actions and Selling Partner facing programs on their long-term business growth. This framework must support development of both homogenous and heterogeneous treatment effect models that can be used to surface impact estimates to Sellers or guide segmented analyses of impact across populations. These models will scale to 200+ different types of actions and a diverse set of use cases (content prioritization, action lift estimation, program valuation).This role requires advising directors/VPs on using causal and impact estimation models to inform key decisions such as whether to maintain support for a feature, or double down on a SP-facing product. This leader must be innovative, determining the right set of techniques to solve the unique scientific challenges, and designing and implementing scalable solutions. The role requires solving problems of significant scientific and technical complexity (often with incomplete data) that necessitates the use and understanding of methodologies across multiple science and econometrics sub-disciplines. This scientist must apply high-judgement to balance the scientific innovation achieving required model accuracy and will often be required to make trade-offs between speed of delivery, breadth of use cases, accuracy of models, clarity of performance metrics, explainability, and other factors.Key job responsibilities- Lead a group of scientists and software engineers to deliver solutions utilizing ML and other advanced algorithms to solve business problems. - Advance team's engineering craftsmanship and drive continued scientific innovation as a thought leader and practitioner. - Develop science and engineering roadmap, run Sprint/quarter and annual planning, and foster cross-team collaboration to execute complex projects. - Design and execute experiments, and analyze experimental results in collaboration with Product Managers, Business Analysts, Economists, and other specialists. - Hire and develop top talents, provide technical and career development guidance to both scientists and engineers in the organization. - Leverage industry best practices to establish repeatable applied science practices, principles & processes. BASIC QUALIFICATIONS- MS degree (or equivalent) in Electrical Engineering, Computer Science, Mathematics, or related technical field- 5+ years of industrial/academic product experience, such as formal verification, program analysis, constraint-solving, and theorem proving- 5+ years of technical management experience- 5+ years of professional software engineering practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations ...

Amazon Web Services (AWS) internships are full-time (40 hours/week) for 12 consecutive weeks during summer. By applying to this position, your application will be considered for all locations we hire for in the United States.Are you excited about Machine Learning, chip acceleration, compilers, storage, systems or EC2? Are you passionate about delivering high quality services that affect hundreds of thousands of users? We are the dubbed the "secret sauce" behind AWS's success with development centers in the U.S. and Israel, and Amazon is at the forefront of innovation by combining cloud scale with the world’s most talented engineers.We hire for multiple disciplines Software and Hardware engineers including but not limited to: compiler engineer, machine learning engineer, runtime engineer, performance engineer and ML chip accelerator, ASIC, physical designs. Because of our teams’ breadth of talent, we’ve been able to improve AWS cloud infrastructure in networking and security with products such as AWS Nitro, Enhanced Network Adapter (ENA), and Elastic Fabric Adapter (EFA), in compute with AWS Graviton and F1 EC2 Instances, in machine learning with AWS Neuron, Inferentia and Trainium ML Accelerators, and in storage with scalable NVMe.If this sounds exciting to you - come build the future with us!Key job responsibilities• Innovating and delivering creative SW Designs to develop new services, solve operational problems, drive improvements in developer velocity, or positively impact operational safety• Writing requirements capturing documents, design documents, integration test plans, and deployment plans• Communicating status and progress of deliverables to schedule, and sharing learnings/ innovations with your team and stakeholdersBASIC QUALIFICATIONS- Currently enrolled in a Bachelor’s degree program or higher Computer Science, Computer Engineering, Electrical Engineering, in these fields are considered with a graduation conferral date between December 2025 and September 2026- Programming experience in internship or coursework with programming language such as Python and/or C or C++.- Candidates with strong interests and academic qualifications/research focus in two of the following: o Distributed systems o Machine Learning - Experience with XLA, TVM, MLIR, LLVM, deep learning models and algorithms o Container o Operating System - Linux system programming/services ...

Shape the Future of Cloud ComputingAre you a graduate student passionate about Automated Reasoning and its real-world applications? Join our team of innovators and embark on a journey to revolutionize cloud computing through cutting-edge automated reasoning techniques.Our tools are called billions of times daily, powering the backbone of Amazon's products and services. We are changing the way computer systems are developed and operated, raising the bar for security, durability, availability, and quality.As an Applied Science Intern, you'll have the opportunity to work alongside our brilliant scientists and contribute to groundbreaking projects. From distributed proof search and SAT/SMT solvers to program analysis, synthesis, and verification, you'll tackle complex challenges at the intersection of theory and practice, driving innovation and delivering tangible value to our customers.This internship is not just about executing tasks – you'll explore novel approaches to solving intricate automated reasoning problems. You'll dive deep into cutting-edge research, leveraging your expertise to develop innovative solutions. You'll work on deploying your solutions into production, witnessing the real-world impact of your contributions.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.Join us and be part of a team that is shaping the future of cloud computing through the power of Automated Reasoning. Apply now and unlock your potential!Amazon has positions available for Automated Reasoning Applied Science Internships in, but not limited to, Arlington, VA; Boston, MA; Cupertino, CA; Minneapolis, MN; New York, NY; Portland, OR; Santa Clara, CA; Seattle, WA; Bellevue, WA; Santa Clara, CA; Sunnyvale, CA.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.Key job responsibilitiesWe are particularly interested in candidates with expertise in: Theorem Proving, Boolean Satisfiability Solvers, Bounded Model Checking, Deductive Verification, Programming/Scripting Languages, Abstract Interpretation, Automated Reasoning, Static/Program Analysis, Program SynthesisBASIC 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 or scripting language like Python, Java, C or C++- Experience with one or more of the following: Theorem Proving, Boolean Satisfiability Solvers, Bounded Model Checking, Deductive Verification, Programming/Scripting Languages, Abstract Interpretation, Automated Reasoning, Static/Program Analysis, Program Synthesis ...

Amazon’s maps play a crucial role in our vehicle navigation, routing, and planning problems to ensure fast and safe deliveries to our customers. As part of the Last Mile Geospatial Science organization, you’ll partner closely with other scientists and engineers in a collegial environment with a clear path to business impact. We have an exciting problem area to augment the maps and routing inputs from satellite/aerial imagery and street videos by leveraging the latest computer vision and deep learning techniques.Key job responsibilitiesSuccessful candidates should have a deep knowledge (both theoretical and practical) of various machine learning algorithms for large scale computer vision problems, the ability to map models into production-worthy code, the communication skills necessary to explain complex technical approaches to a variety of stakeholders and customers, and the excitement to take iterative approaches to tackle big, long term problems. The applied scientist should be proficient with image and video analysis using machine learning, including designing architecture from scratch, modify existing loss functions, full model training, fine-tuning, and evaluating the latest deep learning models. The Applied Scientist optimizes different models for specific platforms, including edge devices with restricted resources. Multi-modal models, e.g., Large Vision Language Models (LVLM), zero-shot, few-shot, and semi-supervised learning paradigms are used extensively.A day in the lifeIf 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!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 Coverage2. Maternity and Parental Leave Options3. Paid Time Off (PTO)4. 401(k) PlanBASIC QUALIFICATIONS- 3+ years of deep learning, computer vision, human robotic interaction, algorithms implementation 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 developing and implementing deep learning algorithms, particularly with respect to computer vision algorithms ...

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. ...