Careers

Join Amazon's Frontier AI & Robotics team and help shape the future of intelligent robotic systems from the inside out. As a Member of Technical Staff - Firmware Engineer, Electronics, you will develop the low-level firmware that brings our in-house robotic actuators to life—writing the embedded code that bridges sophisticated hardware and the high-level AI control systems that power our next-generation robots. Your work will directly enable our robots to see, reason, and act in real-world warehouse environments, making you a critical contributor to one of the most ambitious robotics programs in the world. Key job responsibilities • Develop, test, and optimize embedded firmware for custom in-house robotic actuators, including motor control algorithms (FOC, commutation, current/torque/speed/position loops) running on microcontrollers and DSPs • Design and implement real-time firmware for actuator state estimation, fault detection, and protection logic, ensuring robust and safe operation across all actuator variants deployed in FAR's robotic systems • Collaborate with electronics engineers and motor design engineers to define firmware requirements, hardware interfaces (SPI, I2C, CAN, EtherCAT, RS-485), and actuator bring-up procedures for new hardware revisions • Develop and maintain firmware for field-oriented control (FOC) and sensored/sensorless motor commutation, including tuning current regulators, velocity controllers, and position controllers for high-performance robots • Build and maintain firmware test frameworks and hardware-in-the-loop (HIL) test environments to validate firmware behavior across actuator operating conditions, edge cases, and failure modes • Partner with controls engineers and AI researchers to ensure firmware-level interfaces support high-bandwidth, low-latency communication required by whole-body control and motion planning algorithms • Contribute to actuator firmware architecture decisions, define software-hardware interface standards, and maintain firmware documentation and version control practices to enable scalable multi-actuator development • Support rapid hardware bring-up and debugging of new actuator prototypes, leveraging oscilloscopes, logic analyzers, and custom diagnostic tools to characterize and validate firmware behavior on novel hardware A day in the life Your day is rooted in the intersection of hardware and software where you’ll be wiring firmware from scratch to control custom motors. You might start your morning reviewing firmware behavior logs from the previous night's actuator characterization runs, then spend time working alongside motor design and electronics engineers to debug a torque ripple issue in the motor control loop. In the afternoon, you could be writing and validating embedded firmware for a new actuator variant, tuning (field-oriented control) FOC algorithms, and collaborating with the controls team to ensure firmware interfaces align with high-level motion planning requirements. Beyond the bench, you'll participate in architecture reviews with hardware and software engineers, contribute to code reviews, and document firmware specifications that enable smooth hardware handoffs. You'll be working on actuator variants—each with unique power, torque, and speed requirements—and you'll be the firmware voice in cross-functional design discussions that shape how our actuators are built and controlled. The pace is fast, the problems are novel, and the impact is direct. About the team Frontier AI & Robotics (FAR) is the team at Amazon building the next generation of embodied intelligence. FAR drives the development and implementation of advanced AI models within Amazon’s operations that enable robots to see, reason, and act on the world around them, supporting a number of different warehouse automation tasks.

Our team in Amazon Robotics builds robotic systems that perform contact-rich manipulation tasks safely and reliably in complex, unstructured environments — at Amazon scale. Our scientists and engineers push the boundaries of robotic manipulation to handle enormous object diversity, bringing deep expertise across planning, control, perception, and machine learning. We learn from real-world data at a scale that few teams in robotics can access. We are seeking an Applied Scientist to join our Motion Behaviors team. You will design, implement, and deploy control strategies, manipulation behaviors, and affordance generation methods for contact-rich tasks on robots operating in Amazon fulfillment centers — spanning both engineered and learned approaches. You will validate your work through simulation and real-world testing, leveraging rich operational data to systematically improve system performance. Key job responsibilities • Design, implement, and deploy motion planning, control, and manipulation algorithms on production robotic systems. • Partner with experts across disciplines including perception, hardware and software to create intelligent, integrated systems and solutions. • Contribute to the development of learned manipulation behaviors and controllers, including sim-to-real deployment. • Write production-quality code and own scalable, real-time implementations. • Validate algorithms on hardware, iterating between simulation and real-world testing to ensure robust performance. • Analyze experimental results, identify failure modes, and drive systematic improvements to system performance. • Champion Amazon in academia through publications and scientific presentations. A day in the life Amazon offers a full range of benefits for 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!

Are you a scientist who wants to define how AI remembers people, their loved ones, their unique preferences, and the moments that matter? Are you passionate about NLP, large language models, information retrieval, and entity understanding? Do you want to build systems that learn who the people in a customer's life are, what each of them cares about, and retrieve the right knowledge at the right moment? Do you want access to massive datasets, world-class compute, and the freedom to reason from first principles on novel problems? If any of this excites you, we'd love to talk. Our team is part of Amazon's Personalization organization, building the memory layer that powers how Amazon understands and personalizes for individual customers and their household members. We work at the intersection of NLP, LLMs, entity resolution, and retrieval — disaggregating preferences for each and every customer and their loved ones, and surfacing the most relevant knowledge to power experiences across Amazon that personalize more deeply than ever before. We are a central personalization team, partnering directly with organizations across Amazon to shape how personalization works at scale for years to come. Key job responsibilities As an Applied Scientist in our team, you will be responsible for the research, design, and development of new AI technologies for personalization. You will adopt or invent new machine learning and analytical techniques in the realm of recommendations, information retrieval and large language models. You will collaborate with scientists, engineers, and product partners locally and abroad. Your work will include inventing, experimenting with, and launching new features, products and systems. Please visit https://www.amazon.science for more information.

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 As an Applied Scientist at Prime Video, you will have end-to-end ownership of the product, related research and experimentation, applying advanced machine learning techniques in computer vision (CV), Generative AI, multimedia understanding and so on. You’ll work on diverse projects that enhance Prime Video’s content localization, image/video understanding, and content personalization, driving impactful innovations for our global audience. Other responsibilities include: - Research and develop generative models for controllable synthesis across images, video, vector graphics, and multimedia - Innovate in advanced diffusion and flow-based methods (e.g., inverse flow matching, parameter efficient training, guided sampling, test-time adaptation) to improve efficiency, controllability, and scalability. - Advance visual grounding, depth and 3D estimation, segmentation, and matting for integration into pre-visualization, compositing, VFX, and post-production pipelines. - Design multimodal GenAI workflows including visual-language model tooling, structured prompt orchestration, agentic pipelines. A day in the life Prime Video is pioneering the use of Generative AI to empower the next generation of creatives. Our mission is to make world-class media creation accessible, scalable, and efficient. We are seeking an Applied Scientist to advance the state of the art in Generative AI and to deliver these innovations as production-ready systems at Amazon scale. Your work will give creators unprecedented freedom and control while driving new efficiencies across Prime Video’s global content and marketing pipelines. This is a newly formed team within Prime Video Science!

MULTIPLE POSITIONS AVAILABLE Employer: AMAZON ADVERTISING LLC Offered Position: Applied Scientist II Job Location: New York, New York Job Number: AMZ9935275 Position Responsibilities: 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. Research and implement novel ML and statistical approaches to add value to the business. Mentor junior engineers and scientists. 40 hours / week, 8:00am-5:00pm, Salary Range: $172,400/year to $223,400/year. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, visit: https://www.aboutamazon.com/workplace/employee-benefits. Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation.#0000

Do you want to shape the future of music discovery by building applied science solutions at Amazon scale? Join our Amazon Music team where you'll define and execute the applied science roadmap for catalog and search systems, directly impacting millions of customers worldwide. You'll work at the exciting intersection of large-scale content systems, applied science, and applying the latest advances in foundation models to build an intelligence layer on top of one of the world's largest music and podcast catalogs. As a Principal Applied Scientist, you'll drive innovation in music content understanding, leveraging foundational models to enrich catalog data intelligence and create breakthrough customer experiences. Your work will span across music catalog, search, and data systems teams, where success is measured by customer satisfaction, partner team success, and music labels' ability to share high-quality content seamlessly. Key job responsibilities - Lead the design and implementation of applied science solutions for large-scale music catalog systems, leveraging foundational models to enhance content intelligence and understanding - Define and execute the technical roadmap for Amazon Music catalog and search teams, driving architectural decisions across multiple systems and ensuring alignment with long-term business objectives - Design, propose, and collaborate on experiments that leverage rich music content for enhanced customer experiences in search, personalization, and recommendation systems - Drive technical excellence across three teams (music catalog, music search, music data systems) by conducting design reviews, setting engineering standards, and mentoring senior technical talent - Solve complex problems at the intersection of content systems and applied science, proactively identifying risks and implementing solutions that balance short-term deliverables with long-term architectural maintainability About the team The Amazon Music Catalog and Search team is responsible to help our customers discover the most relevant audio content including music, podcasts and audiobooks. The team invents technology at the intersection of the largest audio catalog in the world, applying latest advances in foundation models and proprietary data assets of Amazon Music. We build technology and products that is deployed worldwide but at the same time is customizable for local markets. We measure our success by the success of our customers, partners and audio content creators.

The Catalog Services Product Knowledge team is seeking a Sr. Applied Science Manager for leading initiatives for understanding, and scaling organization of product schema information. Our vision is simple: build AI systems that are capable of a deep product understanding, so we can organize and scale the catalog metadata (schema) for Amazon e-commerce catalog worldwide. This is a complex problem because the magnitude of products entities (attributes, values, constraints) to be modeled to cover all the Amazon products worldwide. You will lead a team of experienced Applied Scientists (direct reports) to create models and deliver them into the Amazon production ecosystem. Your efforts will build a robust ensemble of ML and GenAI techniques that will scale our catalog artifacts with a high precision across countries and languages. The leader will drive investments in machine learning, natural language processing, GenAI, to solve real world problems at scale. The team's output affects the velocity at which we build product schema and support the largest e-commerce catalog and impact million of customers. The team builds solutions ranging from automatic generation of product metadata, classification of entities, validation of concepts against customer traffic, creation of agents solving complex tasks mimicking human decisions at high precision, etc; all these developments drive true understanding of products at scale. We are looking for an entrepreneurial, experienced Sr. Applied Science Manager who can turn a group of Machine Learning Scientists (PhD's in NLP, ML, GenAI) to produce best in class solutions. The ideal candidate has deep expertise in one or several of the following fields: Generative AI, Agents, LLMs, Web search, Applied/Theoretical Machine Learning, Deep Neural Networks, Classification Systems, Clustering, Natural Language Processing. S/he has a strong publication record at relevant academic venues and proven experience in launching products/features in the industry. Key job responsibilities In this team, you will: - Manage business and technical requirements, design, be responsible for the overall coordination, quality, productivity and will be the primary point of contact for world-wide stakeholders of programs and goals that you lead. - Partner with scientists, economists, and engineers to help deliver scalable ML scaled models, while building mechanisms to help our customers gain and apply insights, and build road maps for the projects you own. - Track service levels and schedule adherence, and ensure the individual stakeholder teams meet and exceed their performance targets. - Be expected to discover, define, and apply scientific, engineering, and business best practices. - Manage and develop Applied Scientists (direct reports with a respective team). About the team The team's mission is to infer knowledge, understand, and derive product schema for all Amazon products entering the Catalog. The work is critical to power drive policies on how products will be merchandised, guide Selling Partners, inform models how to infer attributes. All this information drives the navigational Taxonomy, Search and Detail Page experiences, impacting million of customers. This is an already formed team with experience leading programs spanning services and ML initiatives. The leader collaborates closely with Software Managers, Sr. Leaders, and has exposure to multiple peer teams at Amazon who rely on this team's developments.

We're looking for a Research Scientist to join a team that builds the science behind how Amazon supports its 1.5M+ employees - from forecasting demand across HR services to optimizing how work gets routed and assigned in real time. You'll own high-impact operations research and causal inference work that directly reduces costs and improves the employee experience at global scale. In this role, you will: - Design and build simulation and optimization models that automate workforce scheduling, hiring, and task assignment across Amazon's HR contact centers and back-office operations - Develop causal inference frameworks to measure the true impact of policy changes, product launches, and AI-driven initiatives on employee experience and operational efficiency - Collaborate with senior leaders to translate complex analytical findings into actionable strategies that influence staffing, routing, and resource allocation decisions affecting thousands of associates - Push the boundaries of what's possible by combining operations research with machine learning and generative AI to solve novel workforce optimization problems This isn't a role where you'll be running standard analyses on repeat. You'll be building novel solutions - like contact center simulators that replicate real-world operations, scheduling optimizers that replace manual processes, and experiment frameworks that credibly quantify the impact of large-scale organizational changes. Your work will directly inform decisions made by VP and Director-level leaders who set the strategy for how Amazon supports its employees at scale. About the team We are a team of economists, research scientists, and data scientists within Amazon's People Experience and Technology Finance organization. Our mission is to make Amazon's employee support services smarter, faster, and more efficient through rigorous science - from forecasting models that drive hiring plans to simulation engines that optimize how HR services are delivered to Amazon's global workforce of 1.5M+ people. Our work runs in production, informs weekly planning decisions, and shapes resource allocation at scale. We value intellectual rigor, ownership, and collaboration — publishing at internal science conferences, maintaining shared codebases, and holding each other to high technical standards. You'll have real ownership from day one: framing problems, building solutions, and presenting results to senior leaders who act on your recommendations.

Every day, hundreds of thousands of Amazon associates show up to fulfill the promise we make to our customers. Behind the workforce decisions that support them — staffing, retention, scheduling, development — there should be science that doesn't just describe what happened, but explains why it happened and predicts what comes next. That's the work we do. PXT Central Science (PXTCS) is Amazon's internal research organization dedicated to bringing scientific rigor to people and workforce decisions at global scale. Our team sits within the part of PXTCS that focuses on Amazon's Tier 1 hourly populations — the associates at the heart of Amazon's operations. We are a multidisciplinary group of 15 economists, data scientists, data engineers, and research scientists united by a single mission: to transform complex operational challenges into actionable insights through rigorous causal analysis and predictive modeling that empowers data-driven workforce decisions. We are building something new — causal predictive models that go beyond traditional forecasting. Our models don't just tell leaders what will happen; they reveal why it will happen and what levers they can pull to change the outcome. This is the frontier where causal inference meets modern machine learning, and we need a scientist who can help us push it forward. As a Data Science Manager (DSM), you will lead a team of economists, scientists, and data engineers working to solve complex scientific problems that have high business and customer impact. You will be responsible for building structural and predictive models, leveraging data science workflows, and driving innovations that deliver measurable results for Amazon customers. You will work shoulder-to-shoulder with economists who deeply understand the causal mechanisms driving workforce dynamics and data scientists who know the operational landscape — and you will bring the technical creativity to expand what's possible. That means writing production-quality code that our partner engineering teams can implement into decision-making tools. It means exploring novel feature spaces — large language models, computer vision, and other emerging techniques — to unlock signal that traditional approaches miss. And it means doing all of this with the scientific rigor that causal claims demand. This role is built for someone who is entrepreneurial and energized by ambiguity — someone who sees a prototype model and immediately starts thinking about how to make it robust, scalable, and impactful. You will not just advance your own work; you will elevate the scientists around you. If you want to do science that directly shapes how Amazon supports its workforce — not in theory, but in production systems that leaders use to make better decisions every day — we'd love to talk. Key job responsibilities - Leadership & Team Management: Independently manage and develop a diverse science team, creating an environment that enables consistent delivery and innovation; Build and maintain a high-performing team that can operate effectively and autonomously; Drive strategic growth opportunities for team members, providing paths to demonstrate higher-level scope, impact, and leadership; Establish clear performance metrics and audit mechanisms to track and communicate team progress; Foster a team culture focused on bringing research to production and delivering customer value - Technical & Scientific Direction: Partner with stakeholders and leadership to define and execute the scientific vision for your team; Lead the development of structural and predictive models, leveraging emerging technologies and novel features; Drive the implementation of data science workflows and simulation frameworks; Bridge the gap between science, technology, and business requirements; Leverage the broader Amazon scientific community to enhance team capabilities and knowledge sharing - Strategic Planning & Execution: Define and maintain team structure, strategic direction, and owned technologies; Establish processes that enable consistent delivery and quality of scientific artifacts; Drive reasonable schedules and adjust priorities to ensure optimal outcomes; Create and implement audit mechanisms to track team performance against goals; Remove roadblocks and optimize team productivity - Communication & Influence: Create well-written documents to effectively communicate with technical and non-technical audiences; Influence science and analytics practices across the organization; Build strong partnerships with stakeholders across different business units; Present complex scientific findings to senior leadership; Drive adoption of best practices and innovative solutions About the team The Central Science Team within Amazon’s People Experience and Technology org (PXTCS) uses economics, behavioral science, statistics, machine learning, and Generative AI to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, well-being, and the value of work to Amazonians. We are an interdisciplinary team, which combines the talents of science and UX to develop and deliver solutions that measurably achieve this goal.

Amazon is seeking an exceptional Sr. Applied Scientist to lead the development of perception systems that harness the power of radar and thermal imaging — enabling robots to perceive and operate reliably in conditions where conventional vision alone falls short. In this role, you will develop ML-driven perception pipelines for non-traditional sensing modalities, pushing the boundaries of what robots can see, understand, and act upon in challenging real-world environments. At Amazon, we leverage advanced robotics, machine learning, and artificial intelligence 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. As a Sr. Applied Scientist in Multi-Modal Perception, you will apply deep computer vision expertise alongside classical signal processing techniques for radar and thermal imaging — modalities that provide robustness in adverse conditions and sensing capability beyond the visible spectrum. You will develop ML-based methods to extract semantic and geometric information from radar point clouds, radar tensors, and thermal imagery, and fuse these with camera and depth data to build perception systems that are reliable, comprehensive, and ready for deployment at scale. Your work will unlock new capabilities for our robots — enabling reliable detection, classification, and scene understanding in low-visibility conditions, cluttered environments, and scenarios where traditional RGB-based perception is insufficient. You will lead research that translates cutting-edge advances in deep learning and computer vision to these underexplored but high-impact sensing modalities. Join us in building the next generation of multi-modal perception systems that will define the future of autonomous robotics at scale. Key job responsibilities - Lead the research, design, and development of ML-based perception pipelines for radar and thermal/infrared imaging modalities - Develop deep learning models for object detection, classification, segmentation, and tracking using radar data (point clouds, range-Doppler maps, radar tensors) and thermal imagery - Design and implement multi-modal fusion architectures that combine radar, thermal, camera, and depth data for robust, all-condition perception - Develop novel representations and feature extraction methods tailored to the unique characteristics of radar and thermal sensors (sparsity, noise profiles, spectral properties) - Build end-to-end perception systems — from raw sensor data processing and calibration to model training, evaluation, and real-time deployment - Collaborate closely with Hardware, Navigation, Planning, and Controls teams to define sensor configurations and deliver integrated autonomy solutions - Establish benchmarks, datasets, and evaluation frameworks for radar and thermal perception - Mentor scientists and engineers; foster a culture of scientific rigor, innovation, and high-impact delivery - 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 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.