Careers

The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through 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. We are seeking an Applied Scientist to join our Supply Science team. This team is within the Sponsored Products team, and works on complex engineering, optimization, econometric, and user-experience problems in order to deliver relevant ads on the Amazon search page world-wide thereby enhancing the shopper experience. Our work spans ML and Data science across predictive modeling, reinforcement learning (Bandits), adaptive experimentation, causal inference and data engineering. Key job responsibilities Search Supply and Experiences, within Sponsored Products, is seeking an Applied Scientist to join a team with the mandate of creating new ads experience that elevates the shopping experience for our hundreds of millions of customers worldwide. We are looking for a top analytical mind capable of understanding our complex ecosystem of advertisers participating in a pay-per-click model– and leveraging this knowledge to help turn the flywheel of the business. 
As an Applied Scientist on this team you will: * Drive end-to-end machine learning projects that have a high degree of ambiguity, scale and complexity * Perform analysis on very large data sets to develop ideas and size opportunities; build machine learning models and conduct analysis to demonstrate potential business value * Design A/B experiments, working with engineers to launch online experiments; conduct statistical analysis of the experimental results to derive understanding * Build efficient and automated processes for large-scale feature generation, machine-learning model training, validation and serving. Work with engineers to productionize ML models. * Develop new and innovative machine learning approaches, and collaborate with the science community. A day in the life The successful candidate will be a self-starter comfortable with ambiguity, strong attention to detail and an ability to work in a fast-paced environment. Some examples of day-to-day activities include: * Dive deep into the data to understand business opportunities and formulate the science problems * Implement/create ML models to fit the observed data and predict customer response * Conduct offline analysis to gauge business impact * Communicate with PMs and engineers to discuss experiment plans and outcomes * Work with engineers to conduct A/B tests or productionize your models. * Collaborate with others scientists on problem solving and knowledge sharing. About the team We are a customer-obsessed team of engineers, technologists, product leaders, and scientists. We are focused on continuous exploration of contexts and creatives where advertising delivers value to customers and advertisers. We specifically work on new ads experiences globally with the goal of helping shoppers make the most informed purchase decision. We obsess about our customers and we are continuously innovating on their behalf to enrich their shopping experience on Amazon.

Do you want to join an innovative team of scientists who use machine learning and statistical techniques to create state-of-the-art solutions for providing better value to Amazon’s customers? Do you want to build and deploy advanced ML systems that help optimize millions of transactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data to solve real-world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Machine Learning team for India Consumer Businesses. Machine Learning, Big Data and related quantitative sciences have been strategic to Amazon from the early years. Amazon has been a pioneer in areas such as recommendation engines, ecommerce fraud detection and large-scale optimization of fulfillment center operations. As Amazon has rapidly grown and diversified, the opportunity for applying machine learning has exploded. We have a very broad collection of practical problems where machine learning systems can dramatically improve the customer experience, reduce cost, and drive speed and automation. These include product bundle recommendations for millions of products, safeguarding financial transactions across by building the risk models, improving catalog quality via extracting product attribute values from structured/unstructured data for millions of products, enhancing address quality by powering customer suggestions We are developing state-of-the-art machine learning solutions to accelerate the Amazon India growth story. Amazon India is an exciting place to be at for a machine learning practitioner. We have the eagerness of a fresh startup to absorb machine learning solutions, and the scale of a mature firm to help support their development at the same time. As part of the India Machine Learning team, you will get to work alongside brilliant minds motivated to solve real-world machine learning problems that make a difference to millions of our customers. We encourage thought leadership and blue ocean thinking in ML. Key job responsibilities Use machine learning and analytical techniques to create scalable solutions for business problems Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes Design, develop, evaluate and deploy, innovative and highly scalable ML models Work closely with software engineering teams to drive real-time model implementations Work closely with business partners to identify problems and propose machine learning solutions Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model maintenance Work proactively with engineering teams and product managers to evangelize new algorithms and drive the implementation of large-scale complex ML models in production Leading projects and mentoring other scientists, engineers in the use of ML techniques About the team International Machine Learning Team is responsible for building novel ML solutions that attack India first (and other Emerging Markets across MENA and LatAm) problems and impact the bottom-line and top-line of India business. Learn more about our team from https://www.amazon.science/working-at-amazon/how-rajeev-rastogis-machine-learning-team-in-india-develops-innovations-for-customers-worldwide

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.

Amazon is hiring a Senior Applied Scientist within Customer Forecasting and Valuation (CFV). CFV owns several of the primary decision metrics Amazon uses to evaluate launches and investments — causal estimates of how customer actions today translate into customer value over the year ahead. These metrics are how Amazon works backwards from the customer at scale: they let thousands of launch decisions a year, across Retail, Ads, Marketing, and Selection, weigh short-term profitability against long-term growth. We are in the middle of a generational rebuild of how these metrics are produced. Our team is developing transformer-based foundation models of customer behavior, learned directly from billions of behavioral events. They are being built as shared infrastructure: one learned representation of customer behavior that a wide range of measurement and optimization systems across Amazon can be built on top of. CFV is part of the Customer Behavior Analytics (CBA) organization, which builds the tools used to understand customer behavior and value generation across Amazon's Retail business. As a Senior Applied Scientist you are working at the intersection of causal inference, sequence modeling, and experimentation. The work spans methodological invention — making learned representations estimation-aware, closing the loop between experimental ground truth and model training, extrapolating short-horizon observations into year-ahead causal effects — and translation of that work into production systems that move real launch decisions. You will partner with other senior scientists, product owners, and business leaders, and you will work closely with a dedicated engineering team. The right candidate has deep expertise in ML and causal inference, judgment about when to invent versus reuse, and the appetite to operate in ambiguity. If you want to be part of a team that is shaping how Amazon measures the value of what it does for customers, and how it balances short-term profitability with long-term growth, we should talk.

The Worldwide Design Engineering (WWDE) organization delivers innovative, effective and efficient engineering solutions that continually improve our customers’ experience. WWDE optimizes designs throughout the entire Amazon value chain providing overall fulfillment solutions from order receipt to last mile delivery. We are seeking a Sr. Simulation Scientist to assist in designing and optimizing the fulfillment network concepts and process improvement solutions using discrete event simulations for our World Wide Design Engineering Team. Successful candidates will be technical expert and natural self-starter who have the drive to apply simulation and optimization tools to solve complex flow and buffer challenges during the development of next generation fulfillment solutions. The Simulation Scientist is expected to deep dive into complex problems and drive relentlessly towards innovative solutions working with cross functional teams. Be comfortable interfacing and influencing various functional teams and individuals at all levels of the organization in order to be successful. Lead strategic modelling and simulation projects related to system simulation, optimization, AI powered simulation, advanced simulation tools development, coding simulation algorithms to drive process design decisions. Key job responsibilities - You influence the scientific strategy across multiple teams in your business area. You support go/no-go decisions, build consensus, and assist leaders in making trade-offs. You proactively clarify ambiguous problems, scientific deficiencies, and where your team’s solutions may bottleneck innovation for other teams. - Lead the design, implementation, and delivery of the simulation science solutions to perform system of systems discrete event simulations for significantly complex operational processes that have a long-term impact on a product, business, or function using FlexSim, Demo 3D, AnyLogic or any other Discrete Event Simulation (DES) software packages, AI powered simulation tools, PLC/IPC Emulations, Robotic system simulation and emulation - Lead strategic system modelling and simulation projects using DES tools, software, PLC/IPC emulations, to drive process design decisions - Be an exemplary practitioner in simulation data science discipline to establish best practices and simplify problems to develop discrete event simulations faster with higher standards - Identify and tackle intrinsically hard process flow simulation problems (e.g., highly complex, ambiguous, undefined, with less existing structure, or having significant business risk or potential for significant impact - Deliver artifacts that set the standard in the organization for excellence, from process flow control algorithm design to validation to implementations to technical documents using simulations - Be a pragmatic problem solver by applying judgment and simulation experience to balance cross-organization trade-offs between competing interests and effectively influence, negotiate, and communicate with internal and external business partners, contractors and vendors for multiple simulation projects - Provide simulation data and measurements that influence the business strategy of an organization. Write effective white papers and artifacts while documenting your approach, simulation outcomes, recommendations, and arguments - Lead and actively participate in reviews of simulation data science solutions. You bring clarity to complexity, probe assumptions, illuminate pitfalls, and foster shared understanding within simulation data science discipline - Pay a significant role in the career development of others, actively mentoring and educating the larger simulation data science community on trends, technologies, and best practices - Use advanced statistical /simulation tools and develop codes (python or another object oriented language) for research , simulation, and modeling algorithms - Lead and coordinate simulation efforts between internal teams and outside vendors to develop optimal solutions for the network, including equipment specification, material flow control logic, process design, and site layout - Deliver results according to project schedules and quality A day in the life The day-to-day activities include challenging and problem solving scenario with fun filled environment working with talented and friendly team members. The stakeholders includes Worldwide Design Engineering org verticals, Fulfillment Technology and Robotics team members. The team solve problems related to critical design automation of Material handling equipment and technology design solutions. 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 WWDE Simulation Team’s mission is to apply advanced simulation tools and techniques to drive process flow design, optimization, and improvement for the Amazon Fulfillment Network. We take ownership and pride to come up with simulation based solutions to drive the designs and earn the customer trust. We always strive to invent new ways to simulate and optimize the design and to invent design solutions. We help design and operation engineers to make simulation driven decisions by producing detailed math models and generating key performance metrics.

The Worldwide Design Engineering (WWDE) organization delivers innovative, effective and efficient engineering solutions that continually improve our customers’ experience. WWDE optimizes designs throughout the entire Amazon value chain providing overall fulfillment solutions from order receipt to last mile delivery. We are seeking a Simulation Scientist to assist in designing and optimizing the fulfillment network concepts and process improvement solutions using discrete event simulations for our World Wide Design Engineering Team. Successful candidates will be technical expert and natural self-starter who have the drive to apply simulation and optimization tools to solve complex flow and buffer challenges during the development of next generation fulfillment solutions. The Simulation Scientist is expected to deep dive into complex problems and drive relentlessly towards innovative solutions working with cross functional teams. Be comfortable interfacing and influencing various functional teams and individuals at all levels of the organization in order to be successful. Lead strategic modelling and simulation projects related to drive process design decisions. Key job responsibilities - You influence the scientific strategy across multiple teams in your business area. You support go/no-go decisions, build consensus, and assist leaders in making trade-offs. You proactively clarify ambiguous problems, scientific deficiencies, and where your team’s solutions may bottleneck innovation for other teams. - Lead the design, implementation, and delivery of the simulation data science solutions to perform system of systems discrete event simulations for significantly complex operational processes that have a long-term impact on a product, business, or function using FlexSim, Demo 3D, AnyLogic or any other Discrete Event Simulation (DES) software packages - Lead strategic modeling and simulation research projects to drive process design decisions - Be an exemplary practitioner in simulation science discipline to establish best practices and simplify problems to develop discrete event simulations faster with higher standards - Identify and tackle intrinsically hard process flow simulation problems (e.g., highly complex, ambiguous, undefined, with less existing structure, or having significant business risk or potential for significant impact - Deliver artifacts that set the standard in the organization for excellence, from process flow control algorithm design to validation to implementations to technical documents using simulations - Be a pragmatic problem solver by applying judgment and simulation experience to balance cross-organization trade-offs between competing interests and effectively influence, negotiate, and communicate with internal and external business partners, contractors and vendors for multiple simulation projects - Provide simulation data and measurements that influence the business strategy of an organization. Write effective white papers and artifacts while documenting your approach, simulation outcomes, recommendations, and arguments - Lead and actively participate in reviews of simulation research science solutions. You bring clarity to complexity, probe assumptions, illuminate pitfalls, and foster shared understanding within simulation data science discipline - Pay a significant role in the career development of others, actively mentoring and educating the larger simulation data science community on trends, technologies, and best practices - Use advanced statistical /simulation tools and develop codes (python or another object oriented language) for data analysis , simulation, and developing modeling algorithms - Lead and coordinate simulation efforts between internal teams and outside vendors to develop optimal solutions for the network, including equipment specification, material flow control logic, process design, and site layout - Deliver results according to project schedules and quality A day in the life The dat-to-day activities include challenging and problem solving scenario with fun filled environment working with talented and friendly team members. The internal stakeholders are IDEAS team members, WWDE design vertical and Global robotics team members. The team solve problems related to critical Capital decision making related to Material handling equipment and technology design solutions. 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 World Wide Design EngineeringSimulation Team’s mission is to apply advanced simulation tools and techniques to drive process flow design, optimization, and improvement for the Amazon Fulfillment Network. Team develops flow and buffer system simulation, physics simulation, package dynamics simulation and emulation models for various Amazon network facilities, such as Fulfillment Centers (FC), Inbound Cross-Dock (IXD) locations, Sort Centers, Airhubs, Delivery Stations, and Air hubs/Gateways. These intricate simulation models serve as invaluable tools, effectively identifying process flow bottlenecks and optimizing throughput.

Twitch is looking for an Applied Scientist to lead computer vision and video manipulation work within Amazon Publisher Monetization (APM). You will apply large language models (LLMs), vision-language models (VLMs), and traditional computer vision techniques to build products that directly improve how millions of Twitch creators produce content and how viewers engage with it. This is a high-visibility project backed by senior leadership, and you will have the autonomy to evaluate both first-party and third-party solutions to deliver the highest quality results quickly. If you thrive in a fast-paced, startup-like environment where your scientific decisions shape the product roadmap, we want to hear from you. Key job responsibilities Design and deploy computer vision and video manipulation models using LLMs, VLMs, and traditional techniques, taking solutions from research prototype to production. Partner with senior Product and Twitch leadership to translate customer needs into well-defined scientific problems and deliver end-to-end solutions. Evaluate and integrate generative AI capabilities across Amazon Bedrock and third-party platforms, selecting the approach that maximizes product quality. Drive the team's scientific agenda by proposing new initiatives, authoring technical documents, and contributing to external publications. Mentor fellow scientists and engineers through code reviews, design guidance, and technical assessments that raise the overall quality bar. A day in the life You will split your time roughly evenly between independent research and collaborative sessions. Mornings often start with focused solo work — benchmarking a new VLM, writing model code, or analyzing experiment results. Midday you join working sessions with Product and Twitch leadership to align on requirements or review progress. Afternoons shift between pairing with engineers on production integration and mentoring teammates on evaluation methodology. Weekly science reviews and bi-weekly roadmap syncs keep the team aligned without over-scheduling your calendar. About the team The APM science team supports all of Amazon's Publisher Monetization efforts, building the models and systems behind Twitch's creator tools and ad experiences. The team includes applied scientists, software engineers, and product managers who collaborate daily to move ideas from whiteboard to production. We operate with a startup mentality — moving fast, wearing multiple hats, and iterating closely with Twitch and Product partners. We are accelerating investment in computer vision and generative AI, and this role will be central to that expansion.

Come be a part of a rapidly expanding $35 billion dollar global business. At Amazon Business, a fast-growing startup passionate about building solutions, we set out every day to innovate and disrupt the status quo. We stand at the intersection of tech & retail in the B2B space developing innovative purchasing and procurement solutions to help businesses and organizations thrive. At Amazon Business, we strive to be the most recognized and preferred strategic partner for smart business buying. Bring your insight, imagination and a healthy disregard for the impossible. Join us in building and celebrating the value of Amazon Business to buyers and sellers of all sizes and industries. Unlock your career potential. The Opportunity This is one of the most consequential science leadership roles in Amazon Business. As Applied Science Manager, you will directly influence over $40B in annual revenue by owning the science strategy that powers how we acquire, engage, monetize, and retain millions of business customers worldwide. Your models won't sit in notebooks. They will run in production, shaping real-time decisions across the full customer lifecycle for one of Amazon's fastest-growing businesses. You will operate at the intersection of Business Prime, Marketing Science, and Customer Acquisition three of the highest-visibility, highest-impact charters in the organization. Your work will be presented to VPs and SVPs, inform multi-billion-dollar investment decisions, and fundamentally reshape how Amazon Business goes to market. This is not an incremental optimization role. This is a build-the-future role where your science roadmap becomes the business strategy. What You'll Own Team Leadership & Talent Development: Build and lead a world-class team of applied scientists and research scientists. Set the technical vision, define the multi-year science roadmap, and create an environment where scientists ship models that move the needle on $40B+ in revenue. You will be the bar-raiser who attracts top talent and develops the next generation of science leaders at Amazon. Customer Lifecycle Intelligence ($40B+ Revenue Impact): Own the predictive modeling stack that powers customer identification, targeting, spend behavior forecasting, churn propensity, and declining engagement detection across every Business Prime segment. Your models will determine which customers we invest in, how we invest, and when directly impacting billions in customer lifetime value. Marketing Science & Measurement (Cross-Functional, Multi-Billion Dollar Allocation): Build the causal inference and attribution frameworks that determine how Amazon Business allocates hundreds of millions in marketing investment across paid, owned, and earned channels globally. You will be the single point of science truth for incrementality measurement, marketing mix modeling, and ROI optimization partnering with Marketing, Finance, CPS, and international teams to ensure every dollar drives maximum impact. Customer Acquisition Engine: Lead the science that accelerates new Business Prime member acquisition at scale. Build propensity models, audience optimization systems, and channel effectiveness frameworks that feed directly into acquisition engines serving 10+ global markets. Your work will be the difference between linear growth and exponential growth. Benefits Adoption & the "Aha Moment": Build behavioral segmentation and recommendation systems that identify, for each customer vertical and organizational profile, the exact moment and feature combination that converts a trialist into a loyalist. This is the science of delight at scale. Trust & Safety at Scale: Develop fraud detection models, abuse identification systems, and eligibility classifiers that protect the integrity of the Business Prime ecosystem safeguarding billions in revenue from bad actors. Experimentation & Causal Inference (Organization-Wide): Establish the experimentation frameworks and causal inference methodologies used across the entire Amazon Business organization. Design experiments that measure incremental impact of product launches, pricing changes, and marketing interventions creating the scientific foundation for how leadership makes high-stakes decisions. Why This Role Is Different This is not a role where you optimize a feature in isolation. You will sit at the center of a complex, cross-functional operating model partnering daily with 7+ senior leaders (including Directors and VPs) across Business Prime, CPS Sales, Central Marketing, SSR, GTMO, Finance, and International teams. Your science will be the connective tissue that aligns these organizations around a shared, data-driven growth strategy. You will have direct senior leadership visibility — presenting findings, recommendations, and roadmaps to VP audiences regularly. The insights your team generates will shape OP1/OP2 planning, Board-level narratives, and multi-year investment theses. What We're Looking For The successful Applied Science Manager will have an bias for action in a startup environment, with people leadership skills, a proven ability to build and manage high-performing science teams, define and prioritize research agendas that map to business outcomes, and build methodology and tools that are statistically grounded. You influence product and business strategy through science translating complex analytical findings into crisp, actionable recommendations that senior leaders act on immediately. We are seeking someone who thrives in a fast-paced, high-energy, and fun work environment where we deliver value incrementally and frequently. You are a highly technical leader who knows your subject matter deeply, can elevate the technical bar of your team, and is energized by ambiguity and new problem spaces. You know how to deliver results and show a desire to develop yourself, your colleagues, and your career.

Orchestrating the selection of one out of tens of millions of ads, honoring advertiser targeting intent for hundreds of thousands of advertisers while ensuring great shopper experience for billions of shoppers millions of times per second on a latency of tens of milliseconds is not a trivial task. The demand retrieval team within the Amazon DSP organisation deals with this challenge, developing and operating machine learning models that match ads opportunities with the most relevant ads to deliver the right messages to the right customers at the right time. We are looking for an Applied Scientist to optimize ad matching for Amazon’s programmatic advertisement products. In this role you will lead the design and implementation of solutions for performance sourcing, using behavioural information on customers’ interactions with Amazon and other owned and operated businesses as well as contextual information about the bid request to predict their propensity to convert, in turn driving better advertising campaign outcomes. Your work will affect multi-billion dollar businesses, and you will be responsible for designing, testing and delivering significant breakthrough's for Amazon's business. Successful candidates will have strong technical ability, excellent teamwork, communication skills, and a motivation to achieve business results in a fast-paced environment. Key job responsibilities * Design and implement deep learning models to match the right customers with the right ads across different verticals, geographies, and ads formats. * Investigate new ML techniques such as multi-task learning to ensure that models can operate for a variety of advertisers in multiple industries and with different volumes of conversion events. * Improve the performance, generalisation and scalability of models by introducing new features and enhancing models’ architecture. * Work side by side with our engineers to deliver code changes impacting our ads stack, working with very large datasets and high throughput production systems. * Rapidly prototype and test many possible hypotheses/implementation alternatives in a high-ambiguity environment, making use of both quantitative analysis and business judgement. * Be immersed in Amazon's advertisers and their objectives, and think long-term about how to turn those objectives into products and technical capabilities. * Understand the latest literature on machine learning for recommender and advertising systems, contributing to guiding strategic investment for the organization. A day in the life You will partner with our product and engineering teams, bringing your own ideas to the conversation and aligning on work, adjusting priorities based on business requirements and fast iteration on experiments. You will have a strong theoretical understanding of modern ML techniques and methodologies, and the software engineering and data processing skills to deploy these using the large-scale datasets we deal with in advertising. About the team The Demand Retrieval team is responsible for designing, implementing, deploying and operating machine learning models that match bid opportunities to ads demand based on performance, campaign delivery, and targeting objectives specified by advertisers. We measure the success of our approaches based on offline experimentation and and online metrics that measure the impact of our matching models on campaign KPIs (e.g.: cost per action, return on ads investment, budgets delivered, and targeting precision).

Our organization in Amazon Robotics builds robots that perform contact-rich manipulation 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 experienced Senior Applied Scientist to help guide a small team advancing reinforcement learning for manipulation. We are creating robots that learn how to push, flip, rearrange, and dexterously insert items with unparalleled robustness, speed, and reliability. Our goal is to deploy robots that will work across Amazon's global network and can handle the full diversity of items that Amazon sells. You will set the technical direction for how we learn these behaviors, from simulation training through reliable execution on physical robots, and you will demonstrate new manipulation capabilities on real hardware at scale. This team's mission reaches beyond any single product: to invent and apply manipulation capabilities that generalize to many future robotics applications. The robots our organization already deploys at scale give you a rare proving ground to collect data, run experiments, and get new policies onto real hardware faster than almost anywhere in the field. You will raise the bar for scientific rigor and engineering quality, and mentor other scientists as the team grows. Key job responsibilities - Set the technical direction for learning non-prehensile and contact-rich manipulation policies, from testing the latest advances in the field through demonstrated capability on hardware. - Oversee the development of reinforcement learning approaches that address the long tail of diverse, demanding manipulation conditions. - Own the path from simulation training to reliable, real-time execution on physical robots, making evidence based calls on where learned approaches should replace engineered ones. - Demonstrate new manipulation capabilities on real robots at scale, and turn one-off results into repeatable methods. - Establish the standards, evaluation practices, and data-informed improvement loops that the team builds on. - Mentor scientists and engineers, and raise the bar for applied science rigor and engineering quality. - Partner across control, perception, and hardware to integrate learned behaviors into working systems. - Represent Amazon in academia through publications and scientific presentations. A day in the life Amazon offers a full range of benefits that support you and eligible family members, including domestic partners. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply