Careers

Amazon's Global Procurement Organization is on a mission to transform how procurement works at Amazon scale. We build the technology that powers billions of dollars in purchasing decisions, and We're looking for a Data Science Manager to lead the delivery of technical solutions and programs focused on inventory management of non-inventory supplies across Amazon's global operations. This is a high-impact role at the intersection of technology, operations, and business strategy — where your work directly influences how Amazon procures and manages supplies at scale.

Amazon is seeking exceptional talent to help develop the next generation of advanced robotics systems that will transform automation at Amazon's scale. We're building revolutionary robotic systems that combine innovative AI, sophisticated control systems, and advanced mechanical design to create adaptable automation solutions capable of working safely alongside humans in dynamic environments. This is a unique opportunity to shape the future of robotics and automation at unprecedented scale, working with world-class teams pushing the boundaries of what's possible in robotic manipulation, locomotion, and human-robot interaction. This role presents an opportunity to shape the future of robotics through innovative applications of deep learning and large language models. We leverage advanced robotics, machine learning, and artificial intelligence to solve complex operational challenges at unprecedented scale. Our fleet of robots operates across hundreds of facilities worldwide, working in sophisticated coordination to fulfill our mission of customer excellence. We are pioneering the development of robotics foundation models that: - Enable unprecedented generalization across diverse tasks - Integrate multi-modal learning capabilities (visual, tactile, linguistic) - Accelerate skill acquisition through demonstration learning - Enhance robotic perception and environmental understanding - Streamline development processes through reusable capabilities The ideal candidate will contribute to research that bridges the gap between theoretical advancement and practical implementation in robotics. You will be part of a team that's revolutionizing how robots learn, adapt, and interact with their environment. Join us in building the next generation of intelligent robotics systems that will transform the future of automation and human-robot collaboration. As a Senior Applied Scientist, you will develop and improve machine learning systems that help robots perceive, reason, and act in real-world environments. You will leverage state-of-the-art models (open source and internal research), evaluate them on representative tasks, and adapt/optimize them to meet robustness, safety, and performance needs. You will invent new algorithms where gaps exist. You’ll collaborate closely with research, controls, hardware, and product-facing teams, and your outputs will be used by downstream teams to further customize and deploy on specific robot embodiments. Key job responsibilities As a Senior Applied Scientist in the Foundations Model team, you will: - Leverage state-of-the-art models for targeted tasks, environments, and robot embodiments through fine-tuning and optimization. - Execute rapid, rigorous experimentation with reproducible results and solid engineering practices, closing the gap between sim and real environments. - Build and run capability evaluations/benchmarks to clearly profile performance, generalization, and failure modes. - Contribute to the data and training workflow: collection/curation, dataset quality/provenance, and repeatable training recipes. - Write clean, maintainable, well commented and documented code, contribute to training infrastructure, create tools for model evaluation and testing, and implement necessary APIs - 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. - 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.

We are seeking an Applied Scientist to help build Amazon’s next-generation customer memory and personalization systems. Are you interested in building systems that move beyond reacting to customer behavior, to actually understanding and remembering it over time? Our team is building Amazon’s customer memory layer – a system that extracts, curates, and reasons over customer knowledge to power next-generation personalization. This includes transforming noisy, unstructured signals into durable, high-quality representations of customer preferences, intents, and life events, and using them in real time to improve customer experiences. We are part of Amazon’s Personalization organization, a high-performing group that leverages large-scale machine learning, generative AI, and distributed systems to deliver highly relevant customer experiences. We tackle challenging problems at the intersection of information extraction, knowledge representation, LLM reasoning, and recommendation systems. Our systems operate under real-world constraints of scale, latency, and quality, requiring careful tradeoffs between precision, recall, and responsiveness. This team plays a central role in defining how Amazon understands its customers, and how that understanding is applied across the shopping experience. As an Applied Scientist, you will design and build ML and LLM-powered solutions for Amazon's customer memory and personalization systems. You will work on how customer knowledge is extracted, validated, and applied in production systems. You will own the end-to-end delivery of ML solutions, from problem formulation and modeling to offline and online experimentation, and production deployment at scale. You will deliver high-quality, scalable systems that power customer-facing experiences. You will drive work across areas such as fact extraction, memory quality and lifecycle, temporal reasoning, and grounded personalization, while navigating tradeoffs between quality, latency, and coverage. You will collaborate closely with engineering and product teams to translate research into measurable customer impact. Please visit https://www.amazon.science for more information.

Amazon DynamoDB is a fully managed NoSQL database that serves more than 1 million customers and delivers single-digit millisecond performance at any scale. It supports individual tables over 200TB and sustains over half a million requests per second for hundreds of customers, with up to 99.999% availability. Behind that scale sits a large fleet of capacity that must be placed and balanced continuously. We are looking for an Applied Scientist to advance the science of capacity utilization and data placement across the DynamoDB fleet. You will work backwards from customer experience and fleet economics to find where capacity is used inefficiently, where scaling bottlenecks constrain the service, and where smarter data placement can raise utilization without degrading latency or availability. You will turn these findings into models and algorithms that inform capacity profile decisions and placement policy. You will partner closely with the DynamoDB teams to bring your inputs into production decisions. This is a customer-obsessed science role for a self-driven scientist. Many of the problems are not yet well defined and no textbook solution exists. You will frame the problem, extend state-of-the-art approaches or invent new ones, and drive the work to production impact with a strong bias for action. Key job responsibilities Identify capacity usage optimization opportunities across the DynamoDB fleet. Quantify the customer and cost impact of each opportunity. - Model the scaling bottlenecks of the service and characterize how they constrain placement and utilization. - Develop data placement approaches that balance customer experience (latency, availability, throughput headroom) against optimal capacity utilization. - Partner with the DynamoDB performance team to incorporate your inputs into capacity profile decisions and placement policy. Validate impact with production data. - Build components that integrate directly into production systems or that directly support the large systems making placement and capacity decisions. - Scrutinize the performance of your algorithms and software during implementation. Resolve root causes and leave systems easier to maintain. - Author or co-author papers for internal or external peer-reviewed venues when the work is novel and business considerations allow.

The R2L team is responsible for building the next generation supply chain for Amazon’s world-class ultra-fast customer experiences including Amazon Fresh groceries, Sub-Same Day, Amazon Now, and other soon-to-launch exciting new businesses. Join us and you'll be taking part in serving our customers in as fast as 30 minutes! We are looking for a Data Scientist to join our team and solve some of the most complex business problems! Key job responsibilities - Work with product managers, engineers, other scientists, and leadership to identify and prioritize complex problems. - Interview stakeholders to gather business requirements and translate business problems into data science or analytical problems - Design, develop, and evaluate highly innovative statistics and ML models - Guide and establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation - Proactively seek to identify business opportunities and insights and provide solutions to shape key business processes and policies based on a broad and deep knowledge of Amazon data, industry best-practices, and work done by other teams. A day in the life In this role, you will be a technical expert with significant scope and impact. You will work with Product and Supply Chain Managers, Business Intelligence Engineers, System Developers and other Scientists, to develop models that solve a wide range of complex and ambiguous business problems, with the main goal to improve customer experience, improve availability of products and reduce supply chain cost. A successful Data Scientist will have bias for action needed in a startup environment, with great leadership skills, proven ability to build and manage medium-scale modeling projects, identify data requirements, build methodology and tools that are statistically grounded. It will be a person who enjoys diving deep into data, doing analysis, discovering root causes, and designing long-term scientific solutions. We are seeking someone who can thrive in a fast-paced, high-energy and fun work environment where we deliver value incrementally and frequently. We look for individuals who know how to deliver results and show a desire to develop themselves, their colleagues, and their career. 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: - Medical, Dental, and Vision Coverage - Maternity and Parental Leave Options - Paid Time Off (PTO) - 401(k) Plan If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply! About the team The R2L team is responsible for building the next generation supply chain for Amazon’s world-class ultra-fast customer experiences including Amazon Fresh groceries, Sub-Same Day, Amazon Now, and other soon-to-launch exciting new businesses. Join us and you'll be taking part in serving our customers in as fast as 30 minutes!

Global Optimization is a strategic initiative aimed at improving Amazon advertisers experience at global scale. We are looking for a passionate Applied Scientist to help pioneer the next generation of agentic AI applications for Amazon advertisers. In this role, you will design agentic architectures, develop tools and datasets, and contribute to building systems that can reason, plan, and act autonomously across complex advertiser workflows at global scale. You will work at the forefront of applied AI, developing methods for fine-tuning, reinforcement learning, and preference optimization, while helping create evaluation frameworks that ensure safety, reliability, and trust at scale. You will work backwards from the needs of advertisers—delivering customer-facing products that directly help them create, optimize, and grow their campaigns. Beyond building models, you will advance the agent ecosystem by experimenting with and applying core primitives such as tool orchestration, multi-step reasoning, and adaptive preference-driven behavior. This role requires working independently on ambiguous technical problems, collaborating closely with scientists, engineers, and product managers to bring innovative solutions into production. Key job responsibilities - Design and build agents that improve advertisers experiences globally - Design and implement advanced model and agent optimization techniques, including supervised fine-tuning, instruction tuning and preference optimization (e.g., DPO/IPO). - Design and implement optimization models that work at global scale taking into account nuances of multiple countries - Innovate new science models to help advertisers scale their campaigns globally - Curate datasets and tools for MCP. - Build evaluation pipelines for agent workflows, including automated benchmarks, multi-step reasoning tests, and safety guardrails. - Develop agentic architectures (e.g., CoT, ToT, ReAct) that integrate planning, tool use, and long-horizon reasoning. - Prototype and iterate on multi-agent orchestration frameworks and workflows. - Collaborate with peers across engineering and product to bring scientific innovations into production. - Stay current with the latest research in LLMs, RL, and agent-based AI, optimization and translate findings into practical applications. About the team The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through the latest generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. The Global Optimization team within Sponsored Products and Brands is focused on guiding and supporting 1.6MM advertisers to meet their advertising needs of creating and managing ad campaigns at global scale. At this scale, the complexity of diverse advertiser goals, campaign types, and market dynamics creates both a massive technical challenge and a transformative opportunity: even small improvements in guidance systems can have outsized impact on advertiser success and Amazon’s retail ecosystem. Our work is grounded in state-of-the-art agent architectures, tool integration, reasoning frameworks, and model customization approaches (including tuning, MCP, and preference optimization), ensuring our systems are both scalable and adaptive.

Amazon.com’s Product Detail Page team is looking for talented, motivated and passionate applied scientist to be part of the design and development of a highly scalable multi-tiered shopping application to provide the best possible online shopping experience for Amazon customers world-wide. Our team is comprised of talented applied scientists, developers, testers, program managers, designers and product managers tasked with the singular goal to create THE world's best buying experience. Scientists on this team develop the next-generation technologies and experiences that change how millions interact and shop online. To provide the best possible online shopping at the scale of the web requires ideas from every area of computer science, including distributed computing, large-scale system design, machine learning, natural language processing, data compression and user interface design; the list goes on and is growing every day. We need our scientists to be versatile and always eager to tackle new problems as we continue to push technology forward. Our team leverages sophisticated econometric, machine learning, and big data technologies to help customers to discover the right products at the right prices from millions of trusted sellers billions of times a day. If you are looking for a career-defining opportunity on one of the most customer centric and business impacting teams within Amazon, we’d love to hear from you. We are looking for an Applied Scientist to help build the next generation of Detail Page optimization algorithms. These new set of algorithms will incorporate the continually changing preferences of our customers and continue to scale with numerous new programs that Amazon is introducing for our customers. You will work with multiple Amazon businesses and programs to identify big business opportunities and propose new business features and technical systems to improve customer experience on Amazon Detail Page, Search Page and many other widgets throughout the website. You will be responsible for the quality of algorithm design and will get the opportunity to present your ideas and share results of your deliverables with Amazon executives on a frequent basis. You will get an opportunity to work with senior scientists to define and enforce broad, company-wide technical standards in optimization techniques, statistical modeling and simulation techniques, and/or data analytics.

The Manipulation Robotics Organization at Amazon Robotics is at the forefront of building adaptable and intelligent robotics and manipulating capabilities for Amazon’s fulfillment centers. We have developed and deployed solutions at scale, such as Robin which has sorted more than 3B sorted packages. Our next generation systems include item manipulation systems such as Sparrow which picks and places individual items from cluttered totes. We use state-of-the-art methods in robotics, perception, grasping, generative AI, and behavioral cloning to invent the future for Amazon’s fulfillment centers. We are looking for an Applied Science Manager that is passionate not only about solving today’s complex robotic manipulation problems, but also about shaping and setting the visions for their team, and identifying what are the next set of priorities to tackle. They would partner with a talented and experienced team of applied scientists and engineers that have significant expertise developing and deploying technologies including building foundation models for perception and grasp learning, diffusion policies and sim2real transfer. Key job responsibilities As a manager of the team, you will be working with business partners, applied and research scientists, software development engineers, and product managers to accelerate technology development and and launch new automation solutions for robots across Amazon Robotics. You will have significant influence on our overall strategy by helping define science and engineering strategy, define product features, drive system architecture, and spearhead the best-practices that enable a quality product. You will learn a variety of technologies, development processes, and develop well-rounded skills such as leadership, and effective project management. You will also be accountable for building a strong development team and developing career plans for the scientists and engineers reporting to you. A day in the life Amazon offers a full range of benefits that support you and eligible family members, including domestic partners. 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!

AWS Applied AI Solutions (AAIS) is building toward a future where every business innovates with Amazon AI teammates. To get there, we build AI solutions that improve human capabilities and transform entire business functions. We create end-to-end products that surprise and delight out-of-the-box, making complex things easy and hard things possible, with no cloud experience required. We start with customers who embrace the future and build bridges to meet the rest where they are. We pursue ambitious opportunities with conviction, and we are looking for builders who share that mindset. Do you want to join a brand-new team building an AI system that would disrupt the industry? Do you enjoy dealing with ambiguity and working on hard problems in a fast-paced environment? Amazon Connect is a highly disruptive cloud-based contact center that enables businesses to deliver engaging, dynamic, and personal customer service experiences. With Amazon Connect you can create your own cloud-based contact center and be taking calls in minutes. Amazon Connect leverages the power of Artificial Intelligence and the large ecosystem of AWS services such as Lex, Polly, Lambda, S3, and Kinesis to provide a truly frustration free and natural customer experience. With this technology we are transforming an industry and the way customers interact with businesses and how agents service them. As a Research Scientist on our team you will find optimal combinatorial solutions to very large scale scheduling problems. You will work closely with other senior technical leaders within the team and across AWS. Our team is still at an early stage so you will have significant impact on our deliverables with no operational load from existing models/systems. We have a rapidly growing customer base and an exciting charter in front of us that includes solving highly complex engineering and algorithmic problems. We are looking for passionate, talented, and experienced people to join us to innovate on this new service that addresses customer needs to build modern contact centers in the cloud. The position represents a rare opportunity to be a part of a fast-growing business soon after launch and help shape the technology and product as we grow. You will be playing a crucial role in developing the next generation contact center and get the opportunity to design and deliver scalable, resilient systems while maintaining a constant customer focus. Learn more about Amazon Connect here: https://aws.amazon.com/connect/ About the team Amazon 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. 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. We 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. 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 and AmazeCon conferences, inspire us to never stop embracing our uniqueness. 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.

AWS Applied AI Solutions (AAIS) is building toward a future where every business innovates with Amazon AI teammates. To get there, we build AI solutions that improve human capabilities and transform entire business functions. We create end-to-end products that surprise and delight out-of-the-box, making complex things easy and hard things possible, with no cloud experience required. We start with customers who embrace the future and build bridges to meet the rest where they are. We pursue ambitious opportunities with conviction, and we are looking for builders who share that mindset. Do you want to define the scientific direction for how a global contact-center network forecasts demand, schedules its workforce, and optimizes operations in real time? The Eliza team within Amazon Connect (FCS) is looking for a Principal Research Scientist with a deep operations research specialization to set the research agenda in operations science — combinatorial optimization, queueing theory, stochastic modeling, and forecasting — and to translate that research into production systems that serve millions of customer interactions. As a Principal Research Scientist you will be the senior technical voice for operations research across the org. You will identify the highest-leverage scientific problems, architect novel solutions, and drive them from research through production deployment. You will not sit apart from the work - you will remain deeply hands-on with data, models, and systems while raising the scientific bar for scientists and engineers around you. This is an individual-contributor Principal role: your influence comes from technical depth, invention, and the ability to move business and engineering roadmaps through scientific rigor. You will operate at the intersection of demand forecasting, workforce scheduling, and network optimization - applying combinatorial optimization to large-scale scheduling and resource-allocation problems and queueing theory to model contact-center dynamics under uncertainty, non-stationarity, and competing operational constraints at Internet scale - turning that reasoning into systems that continuously sense, predict, and optimize. Key job responsibilities • Set the multi-year research direction for operations research across contact-center demand prediction, workforce scheduling, and network optimization. • Design and deliver novel algorithms in combinatorial optimization (large-scale scheduling, resource allocation, integer/constraint programming) and queueing theory (contact-center modeling, staffing under stochastic arrivals), alongside stochastic modeling and time-series forecasting, that advance the state of the art while solving real operational problems. • Own end-to-end scientific solutions — from problem formulation and prototyping to production deployment — ensuring robustness, explainability, and seamless integration with existing systems. • Design rigorous experiments and evaluation methodology to validate hypotheses and quantify business impact; establish scientific-excellence mechanisms (metrics, benchmarks, peer review) that the broader science team adopts. • Partner with engineering, product, and operations teams to define data and logging requirements, get them prioritized on roadmaps, and translate scientific capabilities into measurable business outcomes. • Influence senior leadership through written papers and deep-dives, framing complex algorithmic trade-offs in clear business terms. • Mentor and raise the bar for applied and research scientists across the org while maintaining significant hands-on technical contribution. • Represent the team's science externally where appropriate (publications, patents, top-tier venues such as INFORMS, NeurIPS, ICML). A day in the life Your day blends hands-on science with technical leadership. You might spend the morning deep in data and models — prototyping a new combinatorial-optimization formulation for workforce scheduling or a queueing model for staffing under stochastic arrivals against production infrastructure — and the afternoon guiding fellow scientists through a hard optimization or stochastic-modeling problem, reviewing an experiment design, or aligning engineering partners on the data architecture needed to unlock the next capability. You'll drive technical discussions with the team and key stakeholders and periodically write and present papers that shape the business and engineering roadmap. About the team Amazon 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. 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. We 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. 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 and AmazeCon conferences, inspire us to never stop embracing our uniqueness. 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.