Careers

We are seeking a scientist with deep programmatic and Ads experience to further the development and application of analytics methods to examine the complex data flows of the entre Amazon Ads system, and to translate deep-dives into actionable insights for our product teams. In this role you will develop new tools to analyze our advertising data to help improve the performance of our bidding algorithms, targeting and relevance systems, help advance our 3rd party and O&O supply strategy, and evaluate the adoption and impact of feature releases. Key job responsibilities • Analyze data trends regarding supply, optimization, ad load, and advertising mix effects that affect advertiser performance and contribute to achieving advertiser goals. • Present papers to senior leaders on issues like feature development impact on identity recognition rates, and changes of ad selection systems to improve fill rate highlighting insights that will inform our business development and engineering roadmaps. • Formalize our analytics approach to the DSP auctions by analyzing bid spreads, auction depth, and simulating impacts of potential auction structure changes. • Identify, standardize, and operationalize KPIs to effectively measure the performance of all systems involved in ad serving, and use trend insights to inform business priorities. • Partner with engineering teams to define data logging requirements and getting these prioritized in engineering roadmaps. • Validate financial models through analysis. • Develop and own ad revenue and supply intelligence analytics decks that provide ongoing deep-dives. A day in the life The DSP Analytics Leader will work closely with business leaders and engineers on developing common data architecture that will optimize our data logging at different grains, and will allow data interoperability from bid flow to optimization to campaign delivery. The candidate will then analyze the data and present papers and ongoing reports on actionable insights. About the team The DSP Ads Product Analytics Team's Mission: Work alongside those who need product data to apply objective perspective and business logic to uncover insights, advise strategic decisions, and adjust to industry changes.

The Alexa International Science team is looking for a passionate, talented, and inventive Senior Applied Scientist with a strong background in speech models (understanding and generation) and deep learning, to help build industry-leading Generative AI technology with speech-to-speech models and multilingual systems. At this level, you will drive cross-team scientific strategy for speech quality across international locales, influence partner teams, and deliver solutions that have broad impact across Alexa's global products. Key job responsibilities As a Senior Applied Scientist with the Alexa International team, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art in multilingual speech generation, text-to-speech synthesis, and speech-to-speech models. Your work will directly impact customers across multiple languages in the form of natural, expressive, and locale-appropriate voice experiences for Alexa+. You will leverage Amazon's heterogeneous data sources and large-scale computing resources to accelerate advances in speech synthesis, voice quality, and pronunciation accuracy for non-English locales. The ideal candidate possesses a solid understanding of machine learning, speech synthesis (TTS/S2S), multilingual phonetics, modern model architectures, and evaluation methodology. They thrive in a fast-paced environment, tackle complex challenges in low-resource language settings, excel at delivering impactful solutions while iterating based on customer feedback, and are able to influence and align multiple teams around a shared scientific vision for international speech quality. A day in the life You will start your day reviewing experiment results and iterating on model architectures for speech generation. You will collaborate with software engineers to optimize model performance for production deployment, and partner with product managers to align research priorities with customer needs. You will participate in science reviews, paper reading groups, and brainstorming sessions with fellow scientists across the organization. Your work directly impacts how Alexa sounds and communicates with customers in international markets, making every day an opportunity to solve meaningful problems at global scale. About the team The Alexa International Tech team helps Alexa+ global expansion scalable, reliable, and locally relevant for customers. We build the science, engineering, evaluation, and quality platforms behind global AI product delivery: multi-model AI orchestration, multilingual model and data readiness, speech and language quality, reward modeling, synthetic data generation, automated evaluation, developer tooling, defect analysis, and launch mechanisms. Our work sits at the intersection of applied AI, speech, distributed systems, developer experience, and customer quality automation. The goal is simple but hard: help teams build Alexa+ experiences once and scale them across languages, countries, devices, models, and customer expectations without reinventing the same mechanisms every time.

The Alexa International Science team is looking for a passionate, talented, and inventive Applied Science Manager with a strong background in speech models (understanding and generation) and deep learning, to lead a team building industry-leading Generative AI technology with speech-to-speech models and multilingual systems. You will lead a team of Applied Scientists, drive cross-team scientific strategy for speech quality across international locales, influence partner teams, and deliver solutions with broad impact across Alexa's global products. You will own programs with global visibility and interact with a cross-functional group of Science, Product, and Engineering leaders. Your team's work will advance the state of the art in multilingual speech generation, text-to-speech synthesis, and speech-to-speech models, directly impacting customers across 20+ languages with natural, expressive, and locale-appropriate voice experiences for Alexa+. You will leverage Amazon's heterogeneous data sources and large-scale computing resources to accelerate advances in speech synthesis, voice quality, and pronunciation accuracy for non-English locales. The ideal candidate possesses a solid understanding of machine learning, speech synthesis (TTS/S2S), multilingual phonetics, modern model architectures, and evaluation methodology. They thrive in a fast-paced environment, tackle complex challenges in low-resource language settings, and are able to influence and align multiple teams around a shared scientific vision. Core Leadership and Team Management - Lead and manage applied scientists focused on multilingual speech generation and voice personality - Build and develop high-performing science teams focused on speech synthesis, pronunciation, evaluation, and multilingual model adaptation - Set technical direction and raise the bar on scientific rigor, experimental methodology, and publication quality - Hire, mentor, and grow scientists at multiple levels Cross-Organizational Collaboration - Partner with cross org stakeholders to align goals and accelerate delivery - Establish clear communication channels and workflows across organizational boundaries - Drive alignment between science roadmaps and product launch timelines across 20+ locales Delivery and Execution - Own end-to-end delivery of speech quality improvements from research through production deployment - Define success metrics and evaluation frameworks for multilingual speech quality - Balance long-term research investments with near-term launch commitments Key job responsibilities * Lead and manage a team of Applied and Data scientists responsible for building and enhancing capabilities for Alexa+ * Collaborate with cross-functional teams to build methods to align Amazon’s LLMs with human preferences. * Identify and prioritize research opportunities that have the potential to significantly impact our AI systems. * Mentor and guide team members to achieve their career goals and objectives. * Communicate research findings and progress to senior leadership and stakeholders. * Rapidly experiment and drive productisation to deliver customer impact. * Drive academic partnership with top tier Indian university as part of the org’s AI/ML Center initiative. * Participate in and drive science publications in peer-reviewed venues of repute. About the team The Alexa International Science team drives multilingual AI quality for Alexa+, ensuring customers across all supported languages receive a natural, accurate, and culturally appropriate voice experience. We work at the intersection of speech science, LLMs, and international product launches.

We are seeking an Applied Scientist to join Amazon Robotics, Compass Team. In this role, you will own the development of safe legged locomotion algorithms and their deployment on physical hardware, developing learning-based controllers that enable quadrupeds and humanoids to walk, run, and recover from disturbances with agility and robustness. You will leverage Reinforcement Learning (RL), sim-to-real transfer, and other learning-based architectures to train policies that produce stable, dynamic gaits across varied terrains and operating conditions. These learned policies will interface with model-based control strategies to form whole-body control laws that balance performance and safety. Your work sits at the novel intersection of safety and machine learning, where these learned policies will be used in a safety-critical context for complex safety constraints like stability. You will collaborate closely with perception, planning, and safety teams to close the loop between what the robot sees, where it needs to go, and how it moves to get there safely. This is a rare opportunity to shape how legged robots move through the world alongside people. Key job responsibilities • Design, train, and deploy reinforcement learning policies for dynamic legged locomotion including walking, running, stair climbing, and fall recovery on physical quadruped and humanoid platforms • Collaborate with the Compass safety team to ensure locomotion policies operate within safety-critical bounds, incorporating control barrier functions or other formal safety mechanisms as constraints during or after training • Develop sim-to-real transfer pipelines that produce policies robust to the reality gap, including domain randomization, system identification, and adaptive strategies • Integrate learned locomotion policies with model-based whole-body controllers, defining how RL outputs (e.g., joint targets, contact schedules) interface with optimization-based control layers • Formulate reward functions and training curricula that encode both performance objectives and safety constraints, ensuring policies respect stability and contact-force limits • Develop and maintain large-scale training infrastructure for locomotion policy learning, including physics simulation environments and parallelized training pipelines • Evaluate policy performance rigorously through simulation benchmarks, hardware experiments, and failure-mode analysis • Investigate emerging techniques (e.g., foundation models for control, diffusion policies, world models) and assess their applicability to safe legged locomotion • Publish research at top-tier robotics and ML venues and contribute to Amazon's scientific reputation in legged robotics • Collaborate with perception and planning teams to enable terrain-aware and goal-conditioned locomotion behaviors 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.

We are seeking an Applied Scientist to join Compass. In this role, you will own the interface between contact-rich manipulation and the Compass safety software in unstructured environments. You will design learning-based and model-based approaches to contact-rich manipulation when the environment changes unexpectedly. You will collaborate with perception, planning, and controls teams to close the loop from object detection through grasp execution, and you will deploy your algorithms on physical hardware across multiple manipulator platforms. This is an opportunity to define how Amazon's robots safely interact with the physical world: picking, placing, and handling the enormous diversity of objects that flow through our network. Key job responsibilities • Develop and deploy manipulation algorithms for contact-rich tasks and placement across diverse object geometries and material properties • Design force-controlled manipulation strategies that operate safely within Amazon Compass safety constraints • Build reactive manipulation policies that detect and recover from failures (slips, missed grasps, unexpected contacts) in real time • Develop learning-based manipulation policies using RL, imitation learning, or hybrid approaches, and transfer them from simulation to physical hardware • Define and maintain the interface contract between manipulation algorithms and the Compass safety layer, ensuring that grasp and motion plans respect safety bounds without unnecessary conservatism • Collaborate with perception teams to leverage object pose estimation, tactile sensing, and contact detection for closed-loop manipulation • Design simulation environments and training curricula for manipulation policy learning, including realistic contact physics and object diversity • Evaluate manipulation performance through systematic hardware experiments, measuring grasp success rates, cycle times, and safety compliance • Contribute to scientific publications and internal technical documentation • Participate in cross-team design reviews and contribute to the broader manipulation and safety architecture 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.

The Japan Prime & Marketing team drives customer growth and engagement for Amazon Japan. Our applied science team combine advanced machine learning with deep business understanding to deliver experiences that delight customers and grow the Prime membership base in one of Amazon's most dynamic and competitive marketplaces. We are seeking a Senior Applied Scientist to lead the science for personalization and customer growth initiatives across Japan Points, promotional campaigns, and Prime membership engagement. You will own end-to-end science solutions — from problem formulation and data analysis through model development, A/B testing, and production deployment — that directly impact millions of Japanese customers. This is a high-visibility role where you will define the science roadmap, influence business strategy with data-driven insights, and collaborate with product, engineering, economics, and marketing teams across Japan and globally. Key job responsibilities - Define and execute the science roadmap for personalization, points optimization, promotions targeting, and customer growth within Japan Prime & Marketing - Design and develop machine learning models for customer segmentation, lifetime value prediction, churn propensity, and next-best-action recommendation to drive Prime acquisition and retention - Build optimization frameworks for Japan Points allocation, promotional offer targeting, and budget efficiency that maximize long-term customer value rather than short-term engagement - Apply causal inference, experimentation design, and econometric methods to measure the incremental impact of points, promotions, and marketing interventions - Develop personalization systems that tailor offers, messaging, and incentive structures to individual customer preferences and lifecycle stages - Lead the design and analysis of large-scale A/B tests and quasi-experimental studies to validate model performance and business impact - Collaborate with engineering teams to integrate models into production systems with millisecond-level latency requirements serving millions of daily active customers - Influence senior leadership through clear communication of scientific findings, trade-offs, and strategic recommendations - Mentor junior scientists and raise the scientific bar across the team through code reviews, design reviews, and knowledge sharing - Contribute to the broader scientific community through internal and external publications at peer-reviewed venues

We are seeking a Principle Applied Scientist to join Compass. In this role, you will own the perception input into the Compass safety system, defining how robots perceive, interpret, and anticipate their surroundings in safety-critical contexts. You will develop novel approaches to environment understanding that go beyond static scene representation, providing real-time, predictive models of how humans, objects, and dynamic obstacles may evolve over short time horizons. Your work will directly unlock robot performance by replacing conservative assumptions with precise, learned understandings of risk. You will set the scientific direction for perception within Compass, collaborate closely with controls, planning, and firmware teams, and influence the broader Amazon Robotics safety architecture. Key job responsibilities • Define and drive the long-term scientific vision for safety-critical perception within Compass, spanning multiple robot platforms and deployment environments • Develop novel perception algorithms that provide real-time, predictive representations of dynamic environments including human motion forecasting, obstacle trajectory prediction, and scene evolution modeling • Design perception outputs that are tightly coupled to safety constraints, enabling control barrier functions to operate with minimal conservatism while maintaining formal safety guarantees • Research and develop methods to quantify and bound perception uncertainty, providing calibrated confidence estimates that safety systems can reason over • Architect perception pipelines that generalize across sensor modalities (LiDAR, depth cameras, RGB, radar) and robot morphologies without platform-specific retraining • Investigate the application of foundation models and large-scale pre-training to safety-critical perception tasks, establishing when and how learned representations can be trusted at safety-critical confidence levels • Collaborate with controls, motion planning, and firmware teams to define interface contracts between perception and downstream safety modules • Publish research at top-tier venues and represent Amazon Robotics in the broader academic and industry community • Mentor and develop a team of applied scientists and research engineers • Influence Amazon Robotics' safety architecture and perception strategy at the organizational level About the team Work with the inventors of control barrier functions on a novel, universal approach to safe autonomy. 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.

Come build the future of entertainment with us. Are you interested in shaping the future of movies and television? Do you want to define the next generation of how and what Amazon customers are watching? Prime Video is a premium streaming service that offers customers a vast collection of TV shows and movies — all with the ease of finding what they love to watch in one place. We offer customers thousands of popular movies and TV shows from Originals and Exclusive content to exciting live sports events. We also offer our members the opportunity to subscribe to add-on channels which they can cancel at anytime and to rent or buy new release movies and TV box sets on the Prime Video Store. Prime Video is a fast-paced, growth business — available in over 240 countries and territories worldwide. The team works in a dynamic environment where innovating on behalf of our customers is at the heart of everything we do. If this sounds exciting to you, please read on. Prime Video Commerce's mission is to present the right offer to the right customer at the right time — across subscriptions, channels, and transactional video in every market and on every device. Our science team replaces static business rules with ML-driven decisions that personalise the entire commerce journey, from discovery through to checkout and beyond. We operate at scale across hundreds of millions of customers, and we are now expanding into new frontiers — combining the latest advances in agentic and generative AI, behavioural simulation, and causal inference to understand the impact of our decisions before they reach customers. We are looking for an Applied Scientist with a specialism in reinforcement learning and strong machine learning skills to join the Prime Video Commerce Insights team who will work on the latest research and machine learning to build scalable personalisation solutions. You will develop and deploy customer-facing models, understand customer behaviour at scale, and explore emerging techniques that help us make better decisions faster. This is a hands-on role working with a high performing and high visibility multidisciplinary group of engineers and scientists in the London office, focused on improving the customer experience for Prime Video and the wider Amazon organization. You will contribute to the design of machine learning models that scale to large quantities of data and serve low-latency recommendations to all customers worldwide. You will embody scientific rigor in designing and executing experiments to demonstrate the technical efficacy and business value of your methods. You will work alongside a science and engineering team that embodies the customer obsession principle by developing recommendation and decision systems that raise the profile of Prime Video Commerce as a global leader in machine learning and personalisation. Successful candidates will have strong technical ability, a focus on customers by applying a customer-first approach, and excellent teamwork and communication skills. The position offers exceptional opportunities for every candidate to grow their technical and non-technical skills. Key job responsibilities - Strong reinforcement learning skills - Research, design, and implement recommendation systems that personalise across different customer experience touch points. - Collaborate with engineers to deploy and integrate successful model experiment results into large-scale, complex Amazon production systems with low latency. - Provide machine learning thought leadership to both technical and business leaders, with the ability to think strategically about business, product, and technical challenges. - Be a subject matter expert in reinforcement learning approaches for the team and actively contribute to the science roadmap - Define the science roadmap and research agenda that aligns with the organisation's priorities and production constraints. - Work with technical product managers to work backwards from what's important to customers and deliver machine-backed solutions. - Report and share results with the team and wider scientific community by authoring documents that are both statistically rigorous and compellingly relevant, exemplifying good scientific practice in a business environment. A day in the life You will be both a research leader and a hands-on innovator within the Commerce Insights organisation. You'll collaborate with talented engineers and senior leaders to solve problems that are uniquely challenging at Amazon's scale: personalising commerce decisions across multiple business lines balancing competing objectives across offerings, and positively impacting hundreds of millions of customers worldwide. The problems here are technically deep — combining large-scale ML, causal reasoning, and behavioural modelling in a domain where every decision carries real revenue and customer experience consequences. Your research will ship to production and move metrics that matter. About the team You will join a team of great team of engineers and applied scientists with a proven track record of solving highly complex, ambiguous problems — work that has produced patents and publications at top-tier conferences. The team has direct visibility to senior Prime Video leadership, and collaborates broadly across Commerce, Content, and Platform teams to shape how customers discover, subscribe to, and engage with video content. This is a team that operates at the intersection of rigorous research and real-world impact, where your ideas move from whiteboard to production for hundreds of millions of customers.

We are seeking a Member of Technical Staff Simulation Engineer to join our AI robotics research team developing foundation models for robotics. You will rapidly develop 3D physics-based and photorealistic simulations alongside scientists to enable training large-scale machine learning models. Key job responsibilities - Develop simulations for reinforcement learning, closed-loop simulations and synthetic data generation - Implement essential robotics features, including accurate modeling of sensors, actuators, and controllers - Build real-to-sim workflows for dynamic environments and robotics tasks - Implement simulation features to minimize sim-to-real gaps through domain randomization and system identification - Create asset toolchains supporting industry-standard formats (URDF, MJCF, USD) - Collaborate closely with a team of ML researchers to enable large-scale robotics training pipelines About the team At Frontier AI & Robotics (FAR), 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 massive 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.

Alexa AI is looking for an Applied Scientist to build Alexa+, Amazon's LLM-powered conversational assistant. You will work on key initiatives spanning large language model fine-tuning, alignment, agentic reasoning, and evaluation — directly shaping the experience for hundreds of millions of customers worldwide. A successful candidate will be a self-starter comfortable with ambiguity, strong attention to detail, and the ability to work in a fast-paced, ever-changing environment. As an Applied Scientist, you will own the design and development of end-to-end systems. You’ll have the opportunity to create technical roadmaps, and drive production level projects that will support Amazon Science. You will work closely with other scientists and engineers to develop solutions and deploy them into production. The ideal scientist must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. Key job responsibilities * Improve the efficiency of LLM, VLM, and agent training and evaluation pipelines, including distributed training, inference serving, data loading, checkpointing, memory usage, and GPU utilization. * Design, implement, and evaluate novel approaches to LLM fine-tuning, alignment (RLHF, DPO), and distillation for production deployment * Architect agentic systems — multi-step reasoning, tool use, planning, and orchestration * Develop evaluation frameworks and methodologies that go beyond standard benchmarks to capture real-world conversational quality * Translate research advances into customer-facing products, working closely with engineering, product, and cross-functional science teams * Publish results at top-tier venues and represent Amazon in the broader research community About the team Alexa AI is building the science and technology behind Alexa+, Amazon's next-generation conversational assistant. Our team works at the intersection of large language models, reinforcement learning, agentic architectures, and multilingual/multimodal understanding. We operate at massive scale — our models serve customers across dozens of languages and device types. If you want to push the frontier of conversational AI and see your work used by people every day, come join us.