Careers

Amazon Robotics is revolutionizing warehouse automation at unprecedented scale. We are looking for a technical lead to own the whole-body planning, control, and optimization stack for the Phoenix mobile manipulation robot. In this role, you will design and ship motion planners and controllers that coordinate all of Phoenix's degrees of freedom (mobile base, torso, arm, and end-effector) as a single unified system, enabling smooth, safe, and production-ready autonomous manipulation in Amazon fulfillment environments. You will architect whole-body motion planning pipelines (task-and-motion planning, trajectory optimization) that generate collision-free, time-efficient trajectories across the full kinematic chain. You will develop and tune real-time whole-body controllers, including QP-based and model-predictive approaches, and integrate them with the Foundry Controller mainline. A key part of the role is ensuring planner-generated trajectories are high-quality enough to train downstream foundation model policies (e.g., π0.5) at scale. You will also extend Phoenix's Control Barrier Function (CBF) safety architecture, guaranteeing constraint satisfaction from planning through execution. About the team Amazon Robotics develops and deploys advanced robotic systems that power Amazon's fulfillment centers worldwide. Our innovations in mobile manipulation, autonomous navigation, and human-robot collaboration are transforming how products move through our network, enabling faster delivery times while creating safer, more ergonomic work environments for our associates.

Are you passionate about using data science to transform how businesses understand and optimize customer interactions at scale? Do you want to build the models and analytics that power the next generation of AI-driven customer experiences while working directly with customers to accelerate production deployments? As a Senior Applied Scientist within the Applied AI Solutions team, you will collaborate across AI Velocity Teams (AIVT), enabling multiple customer engagements simultaneously. You will lead data science initiatives that span the full lifecycle — from identifying high-value business problems and formulating hypotheses, through rigorous experimentation and modeling, to deploying production-grade solutions that serve thousands of customers. You will bring deep expertise in statistical inference, machine learning, and experimental design to drive measurable impact across Amazon Connect's analytics products and broader Connect AI initiatives. A critical dimension of this role is working directly with customers during production pilots to accelerate time-to-value. You will partner with Applied AI Solutions Architects and Customer Success Specialists to design, build, and deploy AI solutions in customer environments during fixed deployment cycles. You will enable field teams with data-driven insights, reusable analytical assets, ROI tools, and scalable tooling that accelerate customer engagements and solution delivery. Your work will directly influence customer decisions to adopt Connect Customer AI by quantifying business outcomes and demonstrating measurable value. You will operate with significant autonomy, owning the scientific direction of your projects while collaborating with applied scientists, software engineers, product managers, technical, and business stakeholders. You will be expected to identify the right methodology for each problem — whether that's a classical statistical approach, a modern deep learning technique, or a novel combination — and communicate your findings clearly to both technical and non-technical audiences. This role spans Connect AI initiatives including conversational analytics and agentic AI capabilities, offering the opportunity to pioneer data science approaches that scale intelligent analytics worldwide. Key job responsibilities - Design, develop, and deploy statistical models and machine learning pipelines to drive product improvements and business decisions - Work directly with customers during production pilots to design, build, and deploy AI solutions that demonstrate measurable business value - Design and execute A/B experiments and causal inference analyses to measure the impact of new features and model changes on customer outcomes - Build ROI models and business case tools that quantify the value of Connect Customer AI for existing customers transitioning from Connect Customer Basic - Develop and maintain forecasting systems for demand prediction, capacity planning, and workforce optimization - Develop and apply NLP and generative AI techniques to extract insights from structured and unstructured data at scale - Partner with applied scientists and software engineers to productionize models, ensuring reliability, monitoring, and operational excellence - Enable AI Velocity teams with reusable analytical assets, diagnostic notebooks, and scalable tooling that accelerate customer engagements - Build benchmarking studies and optimization frameworks that demonstrate value across customer cohorts - Own success metrics and create mechanisms to measure model performance, adoption, and business impact - Communicate findings and technical trade-offs to senior leadership and customer executives through written documents (6-pagers, science reviews) and presentations - Operate as a shared resource across 2-3 AIVT teams simultaneously, providing data science expertise across multiple customer engagements A day in the life - Start the morning on a call with the AI Velocity Teams preparing for a strategic customer engagement — reviewing the analytical assets and dashboards you've built, walking through how to interpret model outputs, and tailoring recommendations to the customer's contact center environment - Join a customer working session where you're deploying a production pilot — analyzing their historical contact data, building demand forecasting models, and demonstrating how AI optimizations will reduce their cost per serviced contact while improving customer experience metrics - Dive into a deep analysis triggered by AIVT field feedback — a large enterprise customer is seeing unexpected patterns in their contact data, and you're pulling together multi-source data to isolate root cause and build a reusable diagnostic notebook the AIVT team can leverage for similar cases - Participate in a Conversational Analtyics science review, presenting your A/B test results on a new sentiment classification approach and discussing trade-offs between model accuracy and inference latency with the engineering team - Spend the afternoon building a reusable ROI calculator that field teams can use across customer engagements — packaging your economic models with configurable parameters so teams can quickly quantify the value of Connect Customer AI for different customer profiles and usage patterns - Collaborate with AI Architects and Customer Success Specialists across your three active AIVT engagements, providing data science guidance on model selection, evaluation frameworks, and success metrics for each customer's unique use cases - Wrap up by reviewing a design document for an agentic AI feature that will use conversation analytics to automatically surface coaching recommendations for contact center supervisors, providing feedback on the evaluation methodology and success metrics About the team 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 AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do. 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.

The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through cutting-edge 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. Key job responsibilities - Define and lead science initiatives from problem framing through production deployment in a high-ambiguity environment - Develop and deploy models spanning computer vision, language, and search and retrieval that operate on multimodal inputs at scale - Design and analyze large-scale online experiments to measure impact on shopper and advertiser outcomes - Collaborate with engineering, product, and design to ship science into production A day in the life As an Applied Scientist on the Sponsored Videos team, you will tackle problems at the intersection of computer vision, generative AI, search and retrieval, and personalization. You'll own the full science lifecycle from research and experimentation through online testing and production deployment, working closely with engineering, product, and design partners to bring ideas to market. You should be comfortable working with multimodal signals, building models that operate at scale, and measuring impact through rigorous experimentation. Your work will directly influence the experience of hundreds of millions of shoppers and the outcomes of tens of thousands of advertisers. About the team The Sponsored Videos team within Sponsored Products and Brands develops the science and systems behind video advertising experiences that connect advertisers and shoppers across Amazon. We are on a mission to make Amazon the best-in-class destination for shoppers to discover, engage with, and build affinity with brands through videos.

Are you excited to play a strategic role in defining the customer experience on Tablets? Come join a dynamic, customer-obsessed, world-class science team to completely reshape the customer experience on our tablets. Key job responsibilities Using Amazon’s large-scale computing resources, you will design and deploy state-of-the-art recommendation models. You will ask research questions about customer behavior, design state-of-the-art models that help customers discover content, and deploy these models to production alongside other engineers. You will participate in the Amazon ML community and mentor other engineers with a strong interest in and knowledge of ML and generative AI. Your work will directly benefit customers! A day in the life We are looking for a passionate, hard-working, and talented Applied Scientist who has experience developing state-of-the-art models and deploying them to production. You will have an opportunity to make an enormous impact on the design, architecture, and implementation of products used everyday by real customers! About the team The Amazon Tablet team is a world-class team that delivers high-quality, innovative products that are loved by our customers. Our team focuses on spinning many of Amazon’s flywheels with bar-raising mobile experiences on our tablets. Over the last 12 years, we have built 4.0+ star rated products, and we continue to look for ways to scale our business. Join us as we continue our ambitious journey which will give you the opportunity to deliver disruptive products with global impact.

Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video technologist, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! Key job responsibilities - Build sequential decision-making frameworks (e.g., MDPs, multi-armed bandits, dynamic programming) to optimize marketing resource allocation over time under uncertainty. - Create predictive models to forecast marketing efficiency and aid strategic budget allocation across channels, campaigns, and markets. - Design and analyze geo-level and regional hold-out experiments to validate model predictions and establish ground truth. - Automate and scale our modeling infrastructure to improve efficiency and expand coverage across use cases and geographies. - Collaborate with leaders across business and finance teams to translate business questions into well-posed statistical and optimization problems. - Quantify uncertainty in model outputs and communicate results, limitations, and recommendations clearly to non-technical stakeholders. About the team The Marketing Science team drives decision-making on Global Prime Video marketing efforts by delivering sophisticated marketing measurement and optimization models. As an Applied Scientist on the team, you will build optimization and forecasting systems that leverage marketing effectiveness insights to deliver actionable investment recommendations. This includes sequential decision-making frameworks that adapt marketing strategy over time as customer behavior evolves. You will work closely with business and finance stakeholders, as well as other members of our science team, to shape and deliver a roadmap of models. Your frameworks will inform critical decisions for the business.

As part of AI Ops Integration team we have a vision to transform Amazon Operations & Supply Chain into an AI-Native organization by delivering intuitive and differentiated AI solutions that solve enduring operational challenges. We blend vision with curiosity and Amazon's real-world experience to build rapidly AI capabilities. We accelerate our customers' businesses: internal operations teams across Amazon's global footprint through delivery of predictive analytics, LLMs and autonomous AI agents to automate decision-making across Amazon's global operations and supply chain. As an Applied Scientist you will combine state-of-the-art ML/AI techniques with emerging Agentic AI capabilities to build autonomous systems that can understand, reason about, and optimize complex supply chain operations. You will also have the opportunity to work on CV and other relevant technologies. This role combines the excitement of a startup environment with the scale of Amazon Operations. You'll research state-of-the-art open source and internal tools and will tackle highly ambiguous problems. If you thrive on ownership and dealing with ambiguity, passionate about AI and want to fundamentally influence how Amazon Operations leverages AI, this role offers an extraordinary opportunity to make your mark. Key job responsibilities - Lead the development of innovative ML and AI solutions for supply chain and operations - Rapidly prototype and validate new ideas through minimum lovable products (MLPs) - Transform promising prototypes into production-ready systems at global scale - Collaborate with business stakeholders to identify and prioritize high-value automation opportunities - Mentor junior members and promote engineering excellence in AI/ML practices About the team We work back to back to address the technical challenges of automation and intelligence across a variety of products, software, and systems. Our scientists and machine learning engineers work in synergy to solve hard problems and enrich each other's skills. Together, we are a team of worldwide specialists in bringing the potential of practical ML and AI to the max with impact on millions of Amazon customers.

Join us in the evolution of Amazon’s Seller business! The Selling Partner Selection Succ organization is the growth and development engine for our Store. Partnering with business, product, and engineering, we catalyze SP growth with comprehensive and accurate data, unique insights, and actionable recommendations and collaborate with WW SP facing teams to drive adoption and create feedback loops. We strongly believe that any motivated SP should be able to grow their businesses and reach their full potential supported by Amazon tools and resources. We are looking for a Data Scientist II to work on our seller prioritization to improve our SP growth strategy and drive new seller success. As a successful data scientist on our talented team of scientists and economists, you will leverage the latest technology to solve complex problems, and collaborate with engineering, research, and business teams to deliver seller-centric experience on behalf of sour sellers. You need to have deep understanding on the business domain and have the ability to connect business with science. You are also strong in the latest technology and scientific foundation with the ability to collaborate with engineering to put models in production to answer specific business questions. You are an expert at synthesizing and communicating insights and recommendations to audiences of varying levels of technical sophistication. You will continue to contribute to the research community, by working with scientists across Amazon, as well as collaborating with academic researchers and publishing papers (www.aboutamazon.com/research). Key job responsibilities As an Data Scientist II in the team, you will: - Identify opportunities to improve SP growth and translate those opportunities into science problems via principled GenAI solutions . - Design and execute roadmaps for complex science projects to help SP have a delightful selling experience while creating long term value for our shoppers. - Work with our engineering partners and draw upon your experience to meet latency and other system constraints. - Be responsible for communicating our science innovations to the broader internal & external scientific community.

Employer: Amazon Development Center U.S., Inc. Position: Applied Scientist III - AMZ27579.1 Location: New York, NY Multiple Positions Available: Participate in the design, development, evaluation, deployment and updating of data-driven models and analytical solutions for machine learning (ML) and/or natural language (NL) applications. Develop and/or apply statistical modeling techniques (e.g. Bayesian models and deep neural networks), optimization methods, and other ML techniques to different applications in business and engineering. Routinely build and deploy ML models on available data, and run and analyze experiments in a production environment. Identify new opportunities for research in order to meet business goals. Research and implement novel ML and statistical approaches to add value to the business. Mentor junior engineers and scientists. Telecommuting may be permitted. (40 hours / week, 8:00am-5:00pm, Salary Range $183800 - $248700) Amazon.com is an Equal Opportunity – Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation

The Models, Quantum, and Silicon (MQS) Center for Quantum Computing (CQC) is a multi-disciplinary team of scientists, engineers, and technicians, on a mission to develop a fault-tolerant quantum computer. We are looking to hire a Research Software Engineer to join our growing Software team. You will work closely with our experimental physics teams to enable their work characterizing, calibrating, and operating novel quantum devices. The ideal candidate should be able to translate high-level science requirements into software implementations (e.g. Python APIs/frameworks, data analysis pipelines, calibration nodes) that are performant, scalable, and intuitive. This requires someone who (1) has a strong desire to work within a team of scientists and engineers, and (2) demonstrates ownership in initiating and driving projects to completion. This role has a particular emphasis on working directly with experimental physicists to develop scientific software workflows that enable scaling to larger quantum devices. Inclusive Team Culture Here at Amazon, 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. Diverse Experiences Amazon 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. 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. Export Control Requirement Due to applicable export control laws and regulations, candidates must be either a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum, or be able to obtain a US export license. If you are unsure if you meet these requirements, please apply and Amazon will review your application for eligibility. Key job responsibilities - Architect extensible & intuitive frameworks for running quantum computing experiments and analyzing data. - Leverage the latest techniques in quantum calibration to enable scaling to larger devices. - Optimize the performance of experiment & analysis tools to enable faster experiment throughput. - Develop dashboards that allow experimentalists to inspect and control the state of quantum device calibration. - Deploy and maintain cloud infrastructure that supports increasingly-complex science workflows. - Empower scientists to actively contribute to the codebase through mentorship and documentation. We are looking for candidates with strong engineering principles, a bias for action, superior problem-solving, and excellent communication skills. Working effectively within a team environment is essential. As a Research Software Engineer embedded in a broader research science organization, you will have the opportunity to work on new ideas and stay abreast of the field of experimental quantum computation. A day in the life The majority of your time will be spent on projects that extend the functional capabilities or performance of our internal research software stack. This requires working backwards from the needs of our science staff in the context of our larger experimental roadmap. You will translate science and software requirements into design proposals balancing implementation complexity against time-to-delivery. Once a design proposal has been reviewed and accepted, you’ll drive implementation and coordinate with internal stakeholders to ensure a smooth roll out. Because many high-level experimental goals have cross-cutting requirements, you’ll often work closely with other engineers or scientists or on the team. About the team You will be joining the Software group within the MQS Center of Quantum Computing. Our team is comprised of scientists and software engineers who are building scalable software that enables quantum computing technologies.

Alexa Connections is on a mission to become the world's most trusted communication agent — spanning calls, text, email, and the ever-expanding surfaces where people connect. We're building intelligence that keeps customers connected effortlessly while putting their trust and privacy first. As an Applied Scientist, you'll help build the smartest communications agent for people — an agent that understands intent, context, and relationships, and that acts on a customer's behalf to make every interaction feel effortless and genuinely helpful Key job responsibilities You'll research, develop, and ship ML and AI solutions across the communication experience, reasoning over conversational context, intent and needs, and orchestrating large language models and agentic workflows that anticipate how, when, and with whom customers want to connect, and then get it done on their behalf. Whether it's surfacing the right message at the right moment, drafting a reply that sounds like the customer, remembering who matters most to them, or seamlessly carrying a conversation across calls, text, and email, you'll tackle ambiguous, open-ended problems at the intersection of applied science and real-world communication, turning advanced research into features that keep people effortlessly connected to the ones they care about. About the team We're building up the Alexa Connections science team, so you'll join early and grow alongside it. You'll work closely with experienced scientists and engineers invested in your development, with plenty of mentorship, room to broaden your skills, and the chance to own meaningful problems as you grow. It's a supportive place to do impactful work early in your career, shaping how millions of customers connect every day.