Careers

The Amazon Fulfillment Technologies (AFT) Science team is seeking an exceptional Sr. Applied Scientist with strong operations research and optimization expertise to develop production solutions for one of the most complex systems in the world: Amazon's Fulfillment Network. At AFT Science, we design, build, and deploy optimization, statistics, machine learning, and GenAI/LLM solutions that power production systems running across Amazon Fulfillment Centers worldwide. We tackle a wide range of challenges throughout the network, including labor planning and staffing, pick scheduling, stow guidance, and capacity risk management. Our mission is to develop innovative, scalable, and reliable science-driven production solutions that exceed the published state of the art, enabling systems to run optimally and continuously (from every few minutes to every few hours) across our large-scale network. Key job responsibilities As a Senior Applied Scientist, you will collaborate with scientists, software engineers, product managers, and operations leaders to drive the end-to-end lifecycle of optimization-driven solutions that directly impact process efficiency and associate experience in the worldwide fulfillment network. Your key responsibilities include: * Develop deep understanding and domain knowledge of operational processes, system architecture, and business requirements * Dive deep into data and code to identify opportunities for continuous improvement and disruptive new approaches * Design and develop scalable mathematical models for production systems to derive optimal or near-optimal solutions for existing and emerging challenges * Create prototypes and simulations for agile experimentation of proposed solutions * Advocate for technical solutions with business stakeholders, engineering teams, and senior leadership * Partner with software engineers to integrate prototypes into production systems * Design and execute experiments to test new or incremental solutions launched in production * Build and monitor metrics to track solution performance and business impact About the team Amazon Fulfillment Technologies (AFT) designs, develops, and operates end-to-end fulfillment technology solutions that power Amazon Fulfillment Centers worldwide. AFT integrates software, science, and operational processes to optimize how inventory is received, stored, picked, packed, and shipped, enabling Amazon customers to receive the right products at the right time. AFT Science is the central science organization driving scientific solution empowering across all critical AFT charters including inbound, outbound, and labor planning. The Fulfillment Operations Research (FOR) team within AFT Science specializes in optimization, statistics, machine learning, and GenAI/LLM. The team partners closely with software engineering, product, and operations teams to deliver scalable and reliable production solutions while advancing the state of the art in optimization, machine learning, and decision science.

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

Come and be a part of Amazon’s amazing growth story and innovation! Amazon Global Mile Tech is chartered to build a comprehensive portfolio of products that provides Shippers end-to-end transportation, node processing and foundational capabilities to ship packages internationally across a global network of connected arcs and nodes in a variety of scenarios (imports, exports and trans shipments). There are millions of such packages, each with different attributes, delivery requirements and international commerce and customs constraints. What results is a complex graph of source, intermediate and destination nodes with their arcs crossing international borders and associated with different costs and transit times. Accounting for all these constraints and maximizing the number of shipments shipped, while minimizing cost, providing a variety of customer delivery options and maximizing delivery performance is our primary focus. We are building world class technology cutting across deep algorithmic problems, brand new tools that cater to multi-party business scenarios and challenging data models that are evolving very quickly. Our systems touch every single package that travels internationally which mandates building of highly available and scalable distributed systems. Besides technology, there are ample opportunities in the team to build domain expertise of international transportation and supply chain realms and get first-hand experience of the Amazon operations by interacting directly with our global internal and external partners, and of course the esteemed senior engineering talent pool. We are looking for a highly talented applied scientist to be part of our science team in Bellevue, WA. In this role, you will partner with business and technical teams to design and document requirements, and develop technical strategies and software roadmaps for delivery of features. You will be part of passionate group of scientists in optimizing large scale distributed technology solutions and also innovating new ideas and providing technology directions to our business in the domain of imports and exports logistics. We have many key initiatives lined-up to support our rapid evolution and growth of international transportation network by solving some of the most challenging problems in this domain. https://youtu.be/wmjfqQj3UkA Key job responsibilities • Develop accurate and scalable optimization, mathematical programming, and heuristic methods to solve our hardest transportation problems. • Lead and partner with the engineering and operations teams to drive modeling and technical design for complex business problems in transportation. • Lead complex modeling analyses to aid management in making key business decisions and set new policies. • Lead exploration of reinforcement learning techniques to augment optimization algorithms. A day in the life If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply! Benefits: Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan Learn more about our benefits here: https://amazon.jobs/en/internal/benefits/us-benefits-and-stock

We are hiring a Senior Manager, Economics to the Sales Channels team within Amazon Web Services (AWS) Central Econ and Science team. The team partners with the business to optimize sales motions, partner programs, and incentives in multi-sided marketplaces. The problem space includes experimental, quasi-experimental, and observational research design, establishing telemetry for future measurement, and the development of recommendation systems and incentive plans. This role will support a strong team in both sourcing new workstreams and executing existing workstreams. We will consider Applied Scientists with experience working with economists for this role. Key job responsibilities This role interfaces directly with executives, product/program owners, science leadership, and science ICs to create multi-year research agendas that drive step-change growth for the business. As this role is responsible for setting and executing the priorities of a centralized team, stakeholder management, working backward and partnering to work across teams (earns trust) is vital. The team’s mandate includes disambiguating structural relationships, so a strong grounding in applied theory is key to success in this position. The role will also own both production recommendation systems and feature generation for external systems, so experience with production-level development is important. This role will shape the strategic direction of the AWS Central Economics and Science team and collaborate with other science teams at AWS, especially those working on developing policies so that AWS sellers and partners meet customers where they are and help them grow. A day in the life Our team takes big swings and works on hard cross-organizational problems where success is long term and not guaranteed. We expect team members to grow their skills in a supportive and collegial environment. We expect and measure impact, and we hold each other to high standards. We work hard during work hours, but we also don’t encourage working at nights or on weekends: burn out isn’t a successful long run strategy. Because we invest in the long run success of our group it’s important to have hobbies, relax and then come to work refreshed and excited. It makes for bigger impact, faster skill accrual and thus career advancement. About the team Our group is technically rigorous and encourages ongoing academic conference participation and publication. Our leaders are here for you and to enable you to be successful. We believe in being servant leaders focused on influence: good data work has little value if it doesn’t translate into actionable insights that are rolled out and impact the real economy. We emphasize clear, consistent communication since being able to explain what we do ensures high success rates and lowers administrative churn. Also: we laugh a lot. If it’s not fun, what’s the point?

Amazon is building a world class advertising business and defining and delivering a collection of self-service performance advertising products that drive discovery and sales of merchandise. Our products are strategically important to our Retail and Marketplace businesses, driving long-term growth. Sponsored Ads helps merchants, retail vendors, and brand owners grows incremental sales of their products sold on Amazon through native advertising. Sponsored Ads achieves this by using a combination of machine learning, big data analytics, ultra-low latency high-volume engineering systems, and quantitative product focus. If you are looking to make an impact, this is the team for you. You will join a newly-founded team with a broad mandate to experiment and innovate, which will give you the flexibility to develop systems and services from the ground up. As a Principal Applied Scientist in FAIM, you will help build new foundational AI technologies from the ground up and create and launch features for advertisers globally. You will partner with engineers, product managers, TPMs, and senior management to help create these world-class solutions. Most importantly, you will have an opportunity to grow and broaden your technical and scientific skills as you work in an environment that thrives on creativity, experimentation, and collaboration. Key job responsibilities Develop optimization strategies for Full-Funnel Ads Campaigns at Amazon Work with the leadership team on long-range AI/ML plans for Full Funnel Ads Campaigns Help the team adopt the latest SOTA technologies for large scale advertising

Amazon is on a mission to redefine the future of automation — and we're looking for exceptional talent to help lead the way. We are building the next generation of advanced robotic systems that seamlessly blend cutting-edge AI, sophisticated control systems, and novel mechanical design to create adaptable, intelligent automation solutions capable of operating safely alongside humans in dynamic, real-world environments. At Amazon, we leverage the power of machine learning, artificial intelligence, and advanced robotics to solve some of the most complex operational challenges at a scale unlike anywhere else in the world. Our fleet of robots spans hundreds of facilities globally, working in sophisticated coordination to deliver on our promise of customer excellence — and we're just getting started. As a Scientist in Robot Navigation, you will be at the forefront of this transformation — architecting and delivering navigation systems that are intelligent, safe, and scalable. You will bring deep expertise in learning-based planning and control, a strong understanding of foundation models and their application to embodied agents, and as well as have in-depth understanding of control-theoretic approaches such as model predictive control (MPC)-based trajectory planning. You will develop navigation solutions that seamlessly blend data-driven intelligence with principled control-theoretic guarantees. Our vision is bold: to build navigation systems that allow robots to move fluidly and safely through dynamic environments — understanding context, anticipating change, and adapting in real time. You will lead research that bridges the gap between cutting-edge academic advances and production grade deployment, collaborating with world-class teams pushing the boundaries of robotic autonomy, manipulation, and human-robot interaction. Join us in building the next generation of intelligent navigation systems that will define the future of autonomous robotics at scale. Key job responsibilities - Design, develop, and deploy perception algorithms for robotics systems, including object detection, segmentation, tracking, depth estimation, and scene understanding - Lead research initiatives in computer vision, sensor fusion and 3D perception - Collaborate with cross-functional teams including robotics engineers, software engineers, and product managers to define and deliver perception capabilities - Drive end-to-end ownership of ML models — from data collection and labeling strategy to training, evaluation, and deployment - Mentor junior scientists and engineers; contribute to a culture of technical excellence - Define and track key metrics to measure perception system performance in real-world environments - Publish research findings in top-tier venues (CVPR, ICCV, ECCV, ICRA, NeurIPS, etc.) and contribute to patents A day in the life - Train ML models for deployment in simulation and real-world robots, identify and document their limitations post-deployment - Drive technical discussions within your team and with key stakeholders to develop innovative solutions to address identified limitations - Actively contribute to brainstorming sessions on adjacent topics, bringing fresh perspectives that help peers grow and succeed — and in doing so, build lasting trust across the team - Mentor team members while maintaining significant hands-on contribution to technical solutions About the team Our team is a group is a diverse group of scientists and engineers passionate about building intelligent machines. We value curiosity, rigor, and a bias for action. We believe in learning from failure and iterating quickly toward solutions that matter.

Alexa for Shopping (Rufus) is Amazon's new AI-powered shopping assistant that combines the capabilities of Rufus and Alexa+ to provide a more personalized and intelligent shopping experience. We are building the future of AI-powered commerce, where every customer interaction is conversational, personalized, and proactive. We are seeking a Director, Applied Science to lead the science vision and execution for the next-generation conversational AI platform. This leader will own the end-to-end science roadmap for a multi-agent architecture powered by large language models (LLMs), SLMs, reinforcement learning (RL), and post-training optimization to deliver the most helpful, accurate, and fastest AI shopping assistant in the industry. This is a transformational leadership role. You will lead the science that makes this possible: distilling Amazon's vast data assets into rich context, building specialized models through fine-tuning and RL that match frontier model quality at a fraction of the latency, and architecting intelligent agent routing across diverse use cases (pre-purchase, post-purchase, cross-Amazon services). The ideal candidate is deeply steeped in LLM-based architectures, post-training techniques (RLHF, DPO, fine-tuning), and multi-agent systems. They are passionate about applied science, working back from customer experience to define what matters, and building teams that ship production AI at scale. This leader will shape the science philosophy for one of Amazon's highest-visibility AI initiatives. Key job responsibilities - Define and execute the science strategy for Alexa for Shopping conversational AI platform - Lead a large, multidisciplinary organization of Applied Scientists, Research Scientists, and Machine Learning Engineers. - Architect and scale multi-agent systems - Partner with Product, Engineering, and senior leadership (including S-team) to align AI investments with long-term business goals and the vision of conversational commerce replacing traditional shopping paradigms. - Establish scientific best practices across experimentation, evaluation, model iteration, and production deployment for a high-traffic, latency-sensitive customer-facing system. - Mentor and develop senior technical leaders; foster a culture of innovation, customer obsession, and operational excellence.

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 - Lead research and development of speech and audio generation technology and end-to-end speech-to-speech architecture - Develop audio processing solutions for production environments, including source separation, enhancement, and mixing - Define the research roadmap for your area, identify high-impact problems, and communicate technical direction to senior leadership - Publish research, contribute to the broader scientific community, and bring external advances into production systems - Hire, mentor, and develop applied scientists. Grow the team's capabilities to meet evolving customer and business needs About the team This team's mission is to deeply understand all content and empower all customers with relevant language options, innovative accessibility assists, and rich title-information across all their content-experiences on Prime Video. We create and publish content on-time that's meaningful, accurate, and accessible to every customer globally. We delight our customers by pushing the boundaries of content understanding and enrichment. Through inclusion and innovation, we do the most fulfilling work of our career.

We are working on improving shopping on Amazon using the conversational capabilities of large language models and through customer behavioral data to make them more personalized for each customer. We are searching for pioneers who are passionate about technology, innovation, and customer experience, and are ready to make a lasting impact on the industry. In this role, you will be managing a team working on Large Language Model (LLM) and/or Vision-Language Model (VLM) post-training and alignment for new shopping experiences. You’ll be working with talented scientists, engineers, and technical program managers (TPM) to innovate on behalf of our customers. If you’re fired up about being part of a dynamic, driven team, then this is your moment to join us on this exciting journey!

Are you a passionate scientist in the computer vision area who is aspired to apply your skills to bring value to millions of customers? Here at Ring, we have a unique opportunity to innovate and see how the results of our work improve the lives of millions of people and make neighborhoods safer. As an Applied Scientist, you will work with talented peers pushing the frontier of computer vision and machine learning technology to deliver the best experience for our neighbors. This is a great opportunity for you to innovate in this space by developing highly optimized algorithms that will work at scale. This position requires experience with developing Multi-modal LLMs and/or Vision Language Models. You will collaborate with different Amazon teams to make informed decisions on the best practices in machine learning to build highly-optimized integrated hardware and software platforms. Key job responsibilities - Participate in the design, development, evaluation, deployment and updating of data-driven models for computer vision applications. - Research and implement the state-of-the-art computer vision and Vision Language models algorithms. - Collaborate with product managers and engineering teams to design and implement computer vision and machine learning based features for Ring devices - Influence system design and product vision by making informed decisions on the selection of technology, data sources, algorithms, and sensors.