Careers

Join our Frontier AI & Robotics team to support the hardware integration of next-generation robotic systems that will transform how robots perceive and interact with the world. You'll take ownership of hands-on hardware assembly, software integration, and system validation tasks across advanced actuators, precision sensors, and robotic subsystems — ensuring they work seamlessly together to support breakthrough AI research and real-world deployment. Key job responsibilities - Assembly, Integration & DFx — Assemble and integrate robotic hardware (actuators, sensors, vision systems, machined components). Execute assembly processes and test protocols developed with engineering. Provide DFM/DFA feedback and perform simple mechanical/electrical/software design tasks; support integration/debug and partner with engineers to optimize manufacturability and testability. - R&D Prototype Test & Validation — Validate hardware revisions, verify mechanical assemblies, power sequencing, communication interfaces, and peripherals during bring-up. - Debugging & Failure Analysis — Troubleshoot and root-cause issues across the robotic platform (power, compute, comms, actuators, sensors). Conduct failure analysis from component to system level. Reproduce critical failures, interpret schematics, and bridge communication between the lab and engineering teams. - Technical Documentation — Author and maintain runbooks, failure analysis reports, assembly guides, and troubleshooting guides; uphold consistent documentation standards across the lab. - Mechanical Design Support — Perform simple R&D design tasks and test fixture design in CAD, ensuring quality and alignment with engineering priorities. - Lab Operations Support — Support machine shop capabilities, equipment maintenance, inventory management, vendor coordination, and safety/regulatory compliance. - Test Capability Development — Develop test methodologies, design jigs/fixtures, support hardware-in-the-loop (HIL) testing, and streamline failure-to-resolution workflows. A day in the life Your focus centers on the hardware and software that powers our advanced robotic platforms. You'll execute high degree-of-freedom (DoF) robotic prototype assembly and validation, working alongside engineers and fellow technicians. Your responsibilities include building, debugging, validating prototype, performing critical component and assembly quality assessments, providing DFM/DFA feedback to engineers, and designing test jigs and fixtures. Throughout the day, you balance complex assemblies and integration testing while handling urgent prototyping requests, documentation updates, and preparation for upcoming milestones. You're switching between working at the bench, collaborating in design reviews with engineers, and ensuring lab safety and equipment maintenance. About the team At Frontier AI & Robotics, we're not just advancing robotics – we're reimagining it from the ground up. Our team is building the future of intelligent robotics through frontier foundation models and end-to-end learned systems. We tackle some of the most challenging problems in AI and robotics, from developing sophisticated perception systems to creating adaptive manipulation strategies that work in complex, real-world scenarios. What sets us apart is our unique combination of ambitious research vision and practical impact. We leverage Amazon's computational infrastructure and rich real-world datasets to train and deploy state-of-the-art foundation models. Our work spans the full spectrum of robotics intelligence – from multimodal perception using images, videos, and sensor data, to sophisticated manipulation strategies that can handle diverse real-world scenarios. We're building systems that don't just work in the lab, but scale to meet the demands of Amazon's global operations. Join us if you're excited about pushing the boundaries of what's possible in robotics, working with world-class researchers, and seeing your innovations deployed at unprecedented scale.

Have you ever ordered a product on Amazon and when that box with the smile arrived, wondered how it got to you so fast? Wondered where it came from and how much it cost Amazon? If so, the Amazon Global Supply Chain Optimization Technology (SCOT) organization is for you. Watch this video to learn more about our organization, SCOT: http://bit.ly/amazon-scot We are the Optimal Sourcing Systems team (OSS) within SCOT and are looking for a Applied Scientist II to join us! OSS designs and builds systems that measure and manage Amazon’s supplier capabilities, identify and react to supply disruptions, and prioritizes inbound freight for our global network. OSS software is used by every country Amazon services, and is a critical link to ensuring Amazon offers the products our customers want, at the lowest possible cost. This team under OSS orchestrates and tracks inventory movement into Amazon's network, maintains performance feedback loops, and ensures vendor compliance. The Applied Scientist II, in partnership with the Product Management and Tech teams, will lead efforts in following areas: - Build solutions to enable collaborative inventory planning with vendors through agent to agent collaboration or humans-in-the loop collaborative methods - Leverage and develop agentic GenAI workflows to automate the end-to-end vendor coaching and evaluation - Drive the full development cycle from whiteboarding new algorithmic approaches to production-scale deployments - Collaborate with SDEs to build high-performance, distributed training and inference pipelines; translate complex scientific concepts into scalable, production-grade code The ideal candidate thrives in ambiguous problem spaces, relishes working with large volumes of data, and enjoys the challenge of highly complex supply chain contexts. The successful candidate will be a person who has deep understanding about machine learning/reinforcement learning/GenAI models, enjoys and excels at diving into data to analyze root causes, and implementing long term solutions. They can translate complex business logic into scalable models and communicate insights effectively to both technical and non-technical stakeholders. Keys to success in this role include exceptional Science depth and breadth, analytics, statistics, judgment, and communication skills. Experience with supply chain optimization, operations research, or vendor management systems is a plus. Key job responsibilities - Collaborate with product managers, science, and engineering teams to design and implement complex Science solutions for Sourcing Execution & Performance systems - Identify science and innovation opportunities to improve outcomes across Inbound, and guiding the science direction to solve ambiguous business problems. - Build prototypes and core production algorithms, and work with talented engineering teams to scale them. - Drive technical standards and best practices for the team's Science solutions - Mentor and provide technical guidance to other team members on complex projects A day in the life Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 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!

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

We are seeking an Applied Scientist to join Compass. In this role, you will develop the core Control Barrier Function (CBF) algorithms that form the mathematical foundation of the Compass safety system. You will ensure they don't just work in theory but perform reliably on real robots under real-world conditions. You will push the boundaries of concepts central to CBFs: computing robust invariant sets, designing hybrid system formulations that handle contact transitions and mode switches, and developing backup-set approaches that leverage learned policies and multiple controllers. A key challenge of this role is bridging the gap between the mathematics of set invariance and the realities of hardware, including sensor noise, model uncertainty, computational budgets, and discrete state transitions. You will ensure that these algorithms are not only provably correct but also implementable within a safety-critical architecture that must be certified by a third-party. You will contribute directly to the next generation of CBF theory and its practical deployment across Amazon's diverse robot fleet. Key job responsibilities • Develop and implement novel CBF algorithms that provide formal safety guarantees while minimizing conservatism to maximize the permissible operating envelope for each robot platform • Compute and refine invariant sets for complex, high-dimensional robotic systems, developing scalable methods that go beyond what existing analytical approaches can handle • Design formulations for hybrid dynamical systems, handling discrete mode transitions (e.g., contact/no-contact, stance/flight phases) with provable safety across switching boundaries • Address the theory-to-practice gap by developing methods that are robust to model uncertainty, sensor noise, actuation delays, and computational latency • Create reduced-order and full-order dynamics models with both white-box and black-box approach • Implement real-time optimization solvers that execute within the tight timing budgets of safety-critical control loops • Develop formal arguments and documentation sufficient to support third-party safety certification of algorithms • Validate algorithms through rigorous simulation and hardware experiments, characterizing failure modes and quantifying safety margins • Contribute to the theoretical foundations of CBFs through publications at top-tier controls and robotics venues • Collaborate with perception, planning, locomotion, and manipulation teams to accommodate the needs of upstream and downstream systems A day in the life Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply! About the team Work with the inventors of control barrier functions on a novel, universal approach to safe autonomy: one that scales across mobile robots, manipulators, mobile manipulators, and future robot platforms with dynamic stability. You'll push the boundary of safe performance by integrating safety with motion planning, RL, and foundation models, ensuring that safety is never a blocker to robot performance. Your work will underpin robots operating alongside people at Amazon's unprecendented scale.

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!

Amazon.com strives to be Earth's most customer-centric company where customers can shop in our stores to find and discover anything they want to buy. We hire the world's brightest minds, offering them a fast paced, technologically sophisticated and friendly work environment. Economists in the Forecasting, Macroeconomics & Finance field document, interpret and forecast Amazon business dynamics. This track is well suited for economists adept at combining times-series statistical methods with strong economic analysis and intuition. This track could be a good fit for candidates with research experience in: macroeconometrics and/or empirical macroeconomics; international macroeconomics; time-series econometrics; forecasting; financial econometrics and/or empirical finance; and the use of micro and panel data to improve and validate traditional aggregate models. Economists at Amazon are expected to work directly with our senior management and scientists from other fields on key business problems faced across Amazon, including retail, cloud computing, third party merchants, search, Kindle, streaming video, and operations. The Forecasting, Macroeconomics & Finance field utilizes methods at the frontier of economics to develop formal models to understand the past and the present, predict the future, and identify relevant risks and opportunities. For example, we analyze the internal and external drivers of growth and profitability and how these drivers interact with the customer experience in the short, medium and long-term. We build econometric models of dynamic systems, using our world class data tools, formalizing problems using rigorous science to solve business issues and further delight customers.

Amazon.com strives to be Earth's most customer-centric company where customers can shop in our stores to find and discover anything they want to buy. We hire the world's brightest minds, offering them a fast paced, technologically sophisticated and friendly work environment. Economists at Amazon partner closely with senior management, business stakeholders, scientist and engineers, and economist leadership to solve key business problems ranging from Amazon Web Services, Kindle, Prime, inventory planning, international retail, third party merchants, search, pricing, labor and employment planning, effective benefits (health, retirement, etc.) and beyond. Amazon Economists build econometric models using our world class data systems and apply approaches from a variety of skillsets – applied macro/time series, applied micro, econometric theory, empirical IO, empirical health, labor, public economics and related fields are all highly valued skillsets at Amazon. You will work in a fast moving environment to solve business problems as a member of either a cross-functional team embedded within a business unit or a central science and economics organization. You will be expected to develop techniques that apply econometrics to large data sets, address quantitative problems, and contribute to the design of automated systems around the company.

Amazon.com strives to be Earth's most customer-centric company where customers can shop in our stores to find and discover anything they want to buy. We hire the world's brightest minds, offering them a fast paced, technologically sophisticated and friendly work environment. Economists at Amazon partner closely with senior management, business stakeholders, scientist and engineers, and economist leadership to solve key business problems ranging from Amazon Web Services, Kindle, Prime, inventory planning, international retail, third party merchants, search, pricing, labor and employment planning, effective benefits (health, retirement, etc.) and beyond. Amazon Economists build econometric models using our world class data systems and apply approaches from a variety of skillsets – applied macro/time series, applied micro, econometric theory, empirical IO, empirical health, labor, public economics and related fields are all highly valued skillsets at Amazon. You will work in a fast moving environment to solve business problems as a member of either a cross-functional team embedded within a business unit or a central science and economics organization. You will be expected to develop techniques that apply econometrics to large data sets, address quantitative problems, and contribute to the design of automated systems around the company.

Amazon.com strives to be Earth's most customer-centric company where customers can shop in our stores to find and discover anything they want to buy. We hire the world's brightest minds, offering them a fast paced, technologically sophisticated and friendly work environment. Economists at Amazon partner closely with senior management, business stakeholders, scientist and engineers, and economist leadership to solve key business problems ranging from Amazon Web Services, Kindle, Prime, inventory planning, international retail, third party merchants, search, pricing, labor and employment planning, effective benefits (health, retirement, etc.) and beyond. Amazon Economists build econometric models using our world class data systems and apply approaches from a variety of skillsets – applied macro/time series, applied micro, econometric theory, empirical IO, empirical health, labor, public economics and related fields are all highly valued skillsets at Amazon. You will work in a fast moving environment to solve business problems as a member of either a cross-functional team embedded within a business unit or a central science and economics organization. You will be expected to develop techniques that apply econometrics to large data sets, address quantitative problems, and contribute to the design of automated systems around the company.

Amazon.com strives to be Earth's most customer-centric company where customers can shop in our stores to find and discover anything they want to buy. We hire the world's brightest minds, offering them a fast paced, technologically sophisticated and friendly work environment. Economists at Amazon partner closely with senior management, business stakeholders, scientist and engineers, and economist leadership to solve key business problems ranging from Amazon Web Services, Kindle, Prime, inventory planning, international retail, third party merchants, search, pricing, labor and employment planning, effective benefits (health, retirement, etc.) and beyond. Amazon Economists build econometric models using our world class data systems and apply approaches from a variety of skillsets – applied macro/time series, applied micro, econometric theory, empirical IO, empirical health, labor, public economics and related fields are all highly valued skillsets at Amazon. You will work in a fast moving environment to solve business problems as a member of either a cross-functional team embedded within a business unit or a central science and economics organization. You will be expected to develop techniques that apply econometrics to large data sets, address quantitative problems, and contribute to the design of automated systems around the company.