Careers

Welcome to the Worldwide Returns & ReCommerce team (WWR&R) at Amazon.com. WWR&R is an agile, innovative organization dedicated to ‘making zero happen’ to benefit our customers, our company, and the environment. Our goal is to achieve the three zeroes: zero cost of returns, zero waste, and zero defects. We do this by developing groundbreaking products and driving truly innovative operational excellence to help customers keep what they buy, recover returned and damaged product value, keep thousands of tons of waste from landfills, and create the best customer returns experience in the world. We have an eye to the future – we create long-term value at Amazon by focusing not just on the bottom line, but on the planet. We are building the most sustainable re-use channel we can by driving multiple aspects of the Circular Economy for Amazon – Returns & ReCommerce. Amazon WWR&R is comprised of business, product, operational, program, software engineering and data teams that manage the life of a returned or damaged product from a customer to the warehouse and on to its next best use. Our work is broad and deep: we train machine learning models to automate routing and find signals to optimize re-use; we invent new channels to give products a second life; we develop highly respected product support to help customers love what they buy; we pilot smarter product evaluations; we work from the customer backward to find ways to make the return experience remarkably delightful and easy; and we do it all while scrutinizing our business with laser focus. You will help create everything from customer-facing and vendor-facing websites to the internal software and tools behind the reverse-logistics process. You can develop scalable, high-availability solutions to solve complex and broad business problems. We are a group that has fun at work while driving incredible customer, business, and environmental impact. We are backed by a strong leadership group dedicated to operational excellence that empowers a reasonable work-life balance. As an established, experienced team, we offer the scope and support needed for substantial career growth. Amazon is earth’s most customer-centric company and through WWRR&S, the earth is our customer too. Come join us and innovate with the Amazon Worldwide Returns & ReCommerce team! Key job responsibilities 3+ years of scientists or machine learning engineers management experience Knowledge of ML, NLP, Information Retrieval and Analytics 4+ years of building machine learning models or developing algorithms for business application experience 2+ years of programming in Java, C++, Python or related language experience Excellent oral and written communication skills, with the ability to communicate complex technical concepts and solutions to all levels of the organization

Advertising at Amazon is growing incredibly fast and we are responsible for defining and delivering a collection of advertising products that drive discovery and sales. Amazon Business Ads is equally growing fast ($XXXMs to $XBs) and owns engineering and science for the AB WW ad experience. We build business-to-business (“B2B”) specific ad solutions distributed across retail and ad systems for shopper and advertiser experiences. Some include new ad placements or widgets, creatives, sourcing techniques, ad campaign management capabilities and much more! We consider unique AB qualities which are differentiated from the consumer experience such as varying shopper role types, purchasing complexities based on business size and industry (eg education vs healthcare), AB specific features (eg business discounts, buying policies to restrict and prefer products), and AB buyer behaviors (eg buying in bulk). We are seeking a scientific leader who can drive innovation in complex problem areas and new business initiatives. The ideal candidate will: Technical & Research Requirements: * Demonstrate fluency in Python, R, Matlab or other statistical languages and familiarity with deep learning frameworks like PyTorch, TensorFlow * Lead end-to-end solution development from research to prototyping and experimentation * Write and deploy significant parts of scientifically novel software solutions into production Leadership & Influence: * Drive team's scientific agenda by proposing new initiatives and securing management buy-in including PM, SDM * Build consensus on large projects and influence decisions across different teams in Ads Key Leadership Principles: * Dive Deep: Uncover non-obvious insights in data * Deliver Results: Create solutions aligned with customer and product needs * Learn and Be Curious: Demonstrate self-driven desire to explore new research areas * Earn Trust: Build relationships with stakeholders through understanding business needs

Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video subscriptions such as Apple TV+, HBO Max, Peacock, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video team member, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! Key job responsibilities We are looking for passionate, hard-working, and talented individuals to help us push the envelope of content localization. We work on a broad array of research areas and applications, including but not limited to multimodal machine translation, speech synthesis, speech analysis, and asset quality assessment. Candidates should be prepared to help drive innovation in one or more areas of machine learning, audio processing, and natural language understanding. The ideal candidate would have experience in audio processing, natural language understanding and machine learning. Familiarity with machine translation, foundational models, and speech synthesis will be a plus. As an Applied Scientist, you should be a strong communicator, able to describe scientifically rigorous work to business stakeholders of varying levels of technical sophistication. You will closely partner with the solution development teams, and should be intensely curious about how the research is moving the needle for business. Strong inter-personal and mentoring skills to develop applied science talent in the team is another important requirement.

Are you excited about the digital media revolution and passionate about designing and delivering advanced analytics that directly influence the product decisions of Amazon's digital businesses. Do you see yourself as a champion of innovating on behalf of the customer by turning data insights into action? The Amazon Digital Acceleration Analytics team is looking for an analytical and technically skilled individual to join our team. In this role, you will invent, build and deploy state of the art machine-learning models and systems to enable and enhance the team's mission This role offers wide scope, autonomy, and ownership. You will work closely with software engineers & data engineers to put algorithms into practice. You should have strong business judgement, excellent written and verbal communication skills. The candidate should be willing to take on challenging initiatives and be capable of working both independently and with others as a team. Key job responsibilities We are looking for an experienced data scientist with strong foundations in mathematics, statistics & machine learning with exceptional communication and leadership skills, and a proven track record of delivery. In this role, You will Define a long-term science vision and roadmap for the team, driven fundamentally from our customers' needs, translating those directions into specific plans for engineering teams. Design and execute machine learning projects/products end-to-end: from ideation, analysis, prototyping, development, metrics, and monitoring. Drive end-to-end statistical analysis that have a high degree of ambiguity, scale, and complexity. Research and develop advanced Generative AI based solutions to solve diverse customer problems. About the team The MIDAS team operates within Amazon's Digital Analytics (DA) engineering organization, building analytics and data engineering solutions that support cross-digital teams. Our platform delivers a wide range of capabilities, including metadata discovery, data lineage, customer segmentation, compliance automation, AI-driven data access through generative AI and LLMs, and advanced data quality monitoring. Today, more than 100 Amazon business and technology teams rely on MIDAS, with over 20,000 monthly active users leveraging our mission-critical tools to drive data-driven decisions at Amazon scale.

As part of the AI Operations Integration team, we're passionate about pushing the boundaries of AI and transforming how operations teams work. We are looking for an entrepreneurial, experienced, creative, and AI-Native Data Scientist I to join our team. As a Data Scientist I on the AI Operations Integration team, you'll have the opportunity to work on exciting, ambiguous problems that combine Large Language Models (LLMs), Generative AI, and predictive analytics to create intelligent, data-driven operational solutions that fundamentally change how work gets done across Amazon's global operations footprint. You will be responsible for leading the development and delivery of core data science capabilities that power AI-enabled operations. You will have significant influence on our overall strategy by defining analytical approaches, driving solution architecture, and spearheading the data science best practices that enable a high-quality, scalable AI ecosystem. In this role, you'll collaborate with a diverse team of software engineers, AI/ML specialists, operations experts, and technical program managers to develop novel solutions that advance the state of the art in AI-enabled operations. You'll leverage Amazon's vast data resources and computing infrastructure to accelerate development and drive innovation. Your contributions will help define our overall data science strategy, from data enrichment and model optimization to system architecture and best practices, creating a virtuous cycle of AI-enablement that continuously improves operational excellence. Key job responsibilities - Assess and select ideal solution approaches from a wide range of data science methodologies, including machine learning, statistical modeling, NLP, and LLM-based techniques, to solve complex, ambiguous operational problems with significant business impact. - Apply deep expertise to problems involving complex interactions among software systems, data pipelines, and operational processes; design solutions that accurately model these interactions and are extensible, actionable, and easy for others to contribute to. - Own and deliver end-to-end data science solutions for the business with minimal assistance, building a track record of successful launches that drive measurable operational improvements across Amazon's global footprint. - Work closely with operations business teams to deeply understand their challenges, translate ambiguous needs into well-defined problem statements, and ensure data science solutions are grounded in real operational context. - Take the lead on large, cross-functional data science initiatives; drive solutions and influence change across multiple teams connected by shared systems and processes; build consensus among discordant views and align stakeholders on the right path forward. - Make sound scientific and technical trade-offs to meet both short-term operational needs and long-term technology sustainability goals; advocate for the right measurements, sensors, and metadata to ensure solutions are built on reliable signal. - Stay current on data science developments and emerging research; raise awareness of new and well-established techniques across the team; lead knowledge-sharing sessions and mentor data scientists at all levels to help develop the best. - Drive data science best practices, set standards, and proactively lead initiatives to improve operational excellence; identify blind spots in current metrics, challenge assumptions, and restructure data sources to better reflect operational reality. - Partner with engineering and AI/ML teams to integrate data science solutions into existing operational systems; contribute to strategic planning (OP1/QBR/MBR) and advise senior leadership on AI investment priorities and data science strategy. A day in the life You start your morning with a profitability puzzle. Thousands of low-price products are losing money, and no single team can explain why. The buying, placement, and fulfillment systems each say they did the right thing, but the customer's order still ships in three boxes from three warehouses. You trace decisions across systems, find that a parameter was quietly misconfigured weeks ago, and write up the evidence chain. Later you dig into a natural experiment, a recent policy change gave some products broader warehouse coverage. You run a causal analysis to test whether that actually improved shipment consolidation, check the assumptions, and document what you find with confidence intervals and boundary conditions. Not everything is a clean win: the effect is real for products customers buy together, but disappears for standalone items. A couple times a week, you join a cross-team working session where scientists, engineers, and data teams collaborate on end-to-end investigations. You're connecting the dots across systems that don't normally talk to each other tracing a product from purchase order to customer doorstep and pinpointing where value leaks. Some cases have obvious fixes. The more interesting ones are where every system worked as designed but the outcome is still bad. On other days you might build a counterfactual simulation to test whether a different optimization approach would change the economics, design an A/B test to validate it, or present findings to leadership walking them through what you know, what you don't, and what level of confidence each finding carries. The thread that connects it all: you're turning complex cross-system problems into structured evidence that people can act on. Some of that is causal inference, some is building AI-assisted investigation tools (and figuring out where AI helps vs. where it confidently gives you the wrong answer), and some is just good old-fashioned detective work across messy operational data. About the team We're part of a broader organization transforming how global operations teams work through AI. Within that mission, our team focuses on the hardest diagnostic problems: when automated supply chain systems produce bad outcomes and no single team can explain why. We build decision intelligence platforms that traces decisions across automated systems and uses causal engines and AI to find root causes. You'll work alongside scientists, SDEs, and ML engineers, and collaborate regularly with cross-functional partner SMEs. The team is new and you'd help shape it from the ground up.

Come be a part of a rapidly expanding $35 billion-dollar global business. At Amazon Business, a fast-growing startup passionate about building solutions, we set out every day to innovate and disrupt the status quo. We stand at the intersection of tech & retail in the B2B space developing innovative purchasing and procurement solutions to help businesses and organizations thrive. At Amazon Business, we strive to be the most recognized and preferred strategic partner for smart business buying. Bring your insight, imagination and a healthy disregard for the impossible. Join us in building and celebrating the value of Amazon Business to buyers and sellers of all sizes and industries. Unlock your career potential. The AB Go-To-Market Operations Science team (GTMO - Science) is revolutionizing sales productivity through AI-powered solutions. We develop transformative tools that help Account Executives (AEs) to prioritize accounts, recommend product features, and engage more effectively with customers. We partner closely with Product, tech, BI, sales, and marketing teams to launch and scale high-impact global AI products. We're seeking an Applied Scientist to join our team to improve the productivity and efficiency of AEs. You'll be part of expanding GenAI capabilities and scaling its impact across global markets. A successful Applied Scientist at Amazon demonstrates bias for action and operates in a startup environment, with leadership skills, and proven ability to build and manage medium-scale modeling projects, identify data requirements, build methodology and tools that are statistically grounded. We need great leaders to think big and design new solutions to solve complex problems using machine learning (ML) and Generative AI techniques to improve our customers’ experience when using AB. You have hands-on experience making the right decisions about technology, models and methodology choices. Key job responsibilities As an Applied Scientist, you will primarily leverage machine learning techniques and generative AI to outreach customers based on their life cycle stage, behavioral patterns, and purchase history. You may also perform text mining and insight analysis of real-time customer conversations and make the model learn and recommend the solutions. Your work will directly impact the trust customers place in Amazon Business. You will partner with product management and technical leadership to identify opportunities to innovate customer journey experiences. Additional responsibilities include: - Ability to understand a business problem and the available data and identify what statistical or ML techniques can be applied to answer a business question - Design and lead large projects and experiments from beginning to end, and drive solutions to complex or ambiguous problems - Use broad expertise to recommend the right strategies, methodologies, and solve challenges using statistical modeling, machine learning, optimization, and/or other approaches for quantifiable impact on the business - Build models that measure incremental value, predict growth, define and conduct experiments to optimize engagement of AB customers, and communicate insights and recommendations to product, sales, and finance partners. A day in the life In this role, you will be a technical expert with significant scope and impact. You will work with Technical Product Managers, Data Engineers, other Scientists, and Salesforce developers, to build new and enhance existing ML models to optimize customer experience. You will prototype and test new ideas, iterate quickly, and deploy models to production. Also, you will conduct in-depth data analysis and feature engineering to build robust ML models.

Come be a part of a rapidly expanding $35 billion-dollar global business. At Amazon Business, a fast-growing startup passionate about building solutions, we set out every day to innovate and disrupt the status quo. We stand at the intersection of tech & retail in the B2B space developing innovative purchasing and procurement solutions to help businesses and organizations thrive. At Amazon Business, we strive to be the most recognized and preferred strategic partner for smart business buying. Bring your insight, imagination and a healthy disregard for the impossible. Join us in building and celebrating the value of Amazon Business to buyers and sellers of all sizes and industries. Unlock your career potential. The AB Go-To-Market Operations Science team (GTMO - Science) is revolutionizing sales productivity through AI-powered solutions. We develop transformative tools that help Account Executives (AEs) to prioritize accounts, recommend product features, and engage more effectively with customers. We partner closely with Product, tech, BI, sales, and marketing teams to launch and scale high-impact global AI products. We're seeking an Applied Scientist to join our team to improve the productivity and efficiency of AEs. You'll be part of expanding GenAI capabilities and scaling its impact across global markets. A successful Applied Scientist at Amazon demonstrates bias for action and operates in a startup environment, with leadership skills, and proven ability to build and manage medium-scale modeling projects, identify data requirements, build methodology and tools that are statistically grounded. We need great leaders to think big and design new solutions to solve complex problems using machine learning (ML) and Generative AI techniques to improve our customers’ experience when using AB. You have hands-on experience making the right decisions about technology, models and methodology choices. Key job responsibilities As an Applied Scientist, you will primarily leverage machine learning techniques and generative AI to outreach customers based on their life cycle stage, behavioral patterns, and purchase history. You may also perform text mining and insight analysis of real-time customer conversations and make the model learn and recommend the solutions. Your work will directly impact the trust customers place in Amazon Business. You will partner with product management and technical leadership to identify opportunities to innovate customer journey experiences. Additional responsibilities include: - Ability to understand a business problem and the available data and identify what statistical or ML techniques can be applied to answer a business question - Design and lead large projects and experiments from beginning to end, and drive solutions to complex or ambiguous problems - Use broad expertise to recommend the right strategies, methodologies, and solve challenges using statistical modeling, machine learning, optimization, and/or other approaches for quantifiable impact on the business - Build models that measure incremental value, predict growth, define and conduct experiments to optimize engagement of AB customers, and communicate insights and recommendations to product, sales, and finance partners. A day in the life In this role, you will be a technical expert with significant scope and impact. You will work with Technical Product Managers, Data Engineers, other Scientists, and Salesforce developers, to build new and enhance existing ML models to optimize customer experience. You will prototype and test new ideas, iterate quickly, and deploy models to production. Also, you will conduct in-depth data analysis and feature engineering to build robust ML models.

Amazon is looking for a passionate and inventive scientist to advance the science in foundational models and Agentic AI. Specifically, as part of our science team in Amazon AWS Agentic AI, you will lead the research and development of techniques for efficient and effective Agent optimization/learning, through various techniques ranging from model fine-tuning (e.g. RL) to context optimization, as a foundational layer for AWS customers to build reliable and performant Agents. You will have the opportunity to take a product from zero to one by influencing directly the product and science roadmap, and impact millions of our customers. You will also gain hands on experience with Amazon’s large-scale computing resources to accelerate advances in foundation models. Job Responsibility * Develop short-term and long-term science roadmap for research in the broad area of Agent optimization/learning, which could range from RL reward shaping, training efficiency optimization, to automatic prompt optimization and techniques to learn from agent memory. * Develop concrete science plan, implement and validate research idea before moving it to production * Collaborate across product and engineering teams to transfer science innovations into AWS customer facing product. About the team Diverse Experiences AWS 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 Culture Here 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) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’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 Balance We 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 Ads is a multi-billion dollar global business that delivers advertising experiences across Amazon's owned-and-operated properties (including Prime Video, Twitch, Fire TV, and Amazon.com), third-party publisher networks, and emerging channels like generative AI-powered shopping experiences. As one of the fastest-growing segments of Amazon, we operate at unprecedented scale across desktop, mobile, connected TV, and emerging surfaces. Within Amazon Ads, Traffic Quality is a critical pillar of advertiser trust and marketplace integrity. Our mission is to build advanced capabilities that work at petabyte scale to detect sophisticated invalid traffic (IVT) which includes sophisticated non-human traffic, bot networks, and fraudulent engagement patterns across programmatic advertising. We are on a journey to establish Amazon Ads as an industry leader in traffic quality standards and transparency. Our research agenda focuses on staying ahead of adversarial actors through continuous innovation in detection methodologies, leveraging state-of-the-art techniques in deep learning and generative modeling, user behavior and multi-modal representation learning, anomaly detection, time-series analysis, and sparse labeling methods. We process billions of ad events daily, developing novel algorithms that balance precision and recall while operating under strict latency constraints. Our work directly protects hundreds of millions of dollars in advertiser spend annually while maintaining a seamless user experience. Key job responsibilities As an Applied Scientist II in Traffic Quality, you will solve inherently hard problems in advertising fraud detection using deep learning, self-supervised techniques, representation learning, and advanced clustering. You'll work on systems that process billions of ad impressions and clicks per day, using Amazon's cloud services including EC2, S3, EMR, Sagemaker, and RedShift. - Define and frame new research problems in fraud detection where neither problem nor solution is well-defined. - Invent and adapt new machine learning approaches, models, and algorithms to detect sophisticated invalid traffic. - Design and deploy production-quality ML components that directly impact advertiser trust and the business top-line. - Apply domain knowledge to perform broad data analysis as a precursor to modeling and build business insights. - Work with unstructured and massive datasets to deliver results. - Produce research reports meeting top-tier external publication standards. - Contribute to the scientific community through publications at peer-reviewed venues and reviewing research submissions. - Mentor and develop junior scientists on the team. About the team Here are a few papers published by the team: 1/ [Scaling Generative Pre-training for User Ad Activity Sequences. AdKDD 2023.](https://assets.amazon.science/b7/42/03be071743d5a57cb1656e6caa34/scaling-generative-pre-training-for-user-ad-activity-sequences.pdf) 2/ [SLIDR: Real-time Robot Detection On Online Ads, IAAI 2023, Deployed Highly Innovative Applications of AI Track (AAAI 2023)](https://assets.amazon.science/75/2f/3b7106b143f38f7f4d2806388ace/real-time-detection-of-robotic-traffic-in-online-advertising.pdf) 3/ [Self-supervised Representation Learning Across Sequential and Tabular Features Using Transformers, NeurIPS 2022, First Table Representation Learning Workshop](https://openreview.net/forum?id=wIIJlmr1Dsk)

Amazon Robotics is transforming warehouse automation through edge AI and machine learning applied to real-world robotics challenges. We're seeking a Applied Scientist to advance our mobile manipulation capabilities by developing learning-based approaches that enable robots to navigate and manipulate objects in dynamic fulfillment environments. This role offers the opportunity to apply state-of-the-art research to production systems operating at Amazon's unprecedented scale. Key job responsibilities - Model Development and Training: Designing and implementing the model architectures, training and fine tuning the models using various datasets, and optimize the model performance through iterative experiments - Data Management: Process and prepare training data, including data governance, provenance tracking, data quality checks and creating reusable data pipelines. - Experimentation and Validation: Design and execute experiments to test model capabilities on the simulator and on the embodiment, validate performance across different scenarios, create a baseline and iteratively improve model performance. - Code Development: Write clean, maintainable, well commented and documented code, contribute to training infrastructure, create tools for model evaluation and testing, and implement necessary APIs - Research: Stay current with latest developments in foundation models and robotics, assist in literature reviews and research documentation, prepare technical reports and presentations, and contribute to research discussions and brainstorming sessions. - Collaboration: Work closely with senior scientists, engineers, and leaders across multiple teams, participate in knowledge sharing, support integration efforts with robotics hardware teams, and help document best practices and methodologies. A day in the life 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 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 team Are you inspired by invention? Is problem solving through teamwork in your DNA? Do you like the idea of seeing how your work impacts the bigger picture? Answer yes to any of these and you’ll fit right in here at Amazon Robotics. We are a smart, collaborative team of enthusiastic doers that work passionately to apply innovative advances in robotics and software to solve real-world challenges that will transform our customers’ experiences in ways we can’t even image yet. We invent new improvements every day. We are Amazon Robotics and we will give you the tools and support you need to invent with us in ways that are rewarding, fulfilling and fun!