Careers

We are seeking a Robotics/AI Motor Control Scientist to develop cutting-edge machine learning algorithms for motor control systems in robots. In this role, you will focus on creating and optimizing intelligent motor control strategies to enable robots to perform complex, whole-body tasks. Your contributions will be essential in advancing robotics by enabling fluid, reliable, and safe interactions between robots and their environments. Key job responsibilities - Develop controllers that leverage reinforcement learning, imitation learning, or other advanced AI techniques to achieve natural, robust, and adaptive motor behaviors - Collaborate with multi-disciplinary teams to integrate motor control systems with robotic hardware, ensuring alignment with real-world constraints such as actuator dynamics and energy efficiency - Use simulation and real-world testing to refine and validate control algorithms - Stay updated on advancements in robotics, AI, and control systems to apply advanced techniques to robotic motion challenges - Lead technical projects from conception through production deployment - Mentor junior scientists and engineers - Bridge research initiatives with practical engineering implementation About the team Fauna Robotics, an Amazon company, is building capable, safe, and genuinely delightful robots for everyday life. Our goal is simple: make robots people actually want to live and interact with in everyday human spaces. We believe that future won’t arrive until building for robotics becomes far more accessible. Today, too much effort is spent reinventing the fundamentals. We’re changing that by developing tightly integrated hardware and software systems that make it faster, safer, and more intuitive to create real-world robotic products. Our work spans the full stack: mechanical design, control systems, dynamic modeling, and intelligent software. The focus is not just functionality, but experience. We’re building robots that feel responsive, expressive, and genuinely useful. At Fauna, you’ll work at the frontier of this space, helping define how robots move, manipulate, and interact with people in natural environments. It’s an opportunity to solve hard problems across hardware and software with a team focused on making robotics accessible and joyful to build. If you care about making robotics real for everyone and building systems that are as delightful as they are capable, we’re interested in hearing from you. an opportunity to solve hard problems across hardware and software with a team focused on making robotics accessible and joyful to build. If you care about making robotics real for everyone and building systems that are as delightful as they are capable, we’re interested in hearing from you.

Amazon Braket is investing in fault-tolerant quantum computing capabilities. We are looking for an Applied Scientist to own resource estimation and workload benchmarking for fault-tolerant quantum workloads on AWS. You will answer the fundamental questions: how many physical qubits are needed, what gate depths are achievable, and what error budgets are realistic for a given algorithm on a given device. Your models will inform technical decisions, customer conversations, and our roadmap. This role requires more than resource estimation methodology alone. You need a broad foundation in quantum error correction research to reason about the full picture: how code choices affect resource requirements, how logical circuit structure impacts physical costs, and how benchmarking results feed back into the system. You will be part of a small team of scientists and engineers, and we expect you to codify your solutions in production-quality code and contribute directly to the codebase alongside your teammates. Key job responsibilities - Build and maintain FTQC resource estimation models that determine qubit counts, gate depths, and error budgets for target algorithms - Develop benchmarking frameworks that evaluate compilation quality against realistic hardware constraints - Produce resource estimates that inform technical decisions and feed into customer readiness work led by the Applications & Engagement team - Collaborate with the QEC compilation scientists on how resource estimates feed back into code selection and optimization - Connect benchmarking outputs to published materials in coordination with Braket's science and product teams - Stay current with the rapidly evolving QEC literature and incorporate new results into estimation models

Amazon Braket is investing in fault-tolerant quantum computing capabilities. We are looking for a Senior Applied Scientist with deep expertise in quantum error correction to work on compilation science as part of a team of scientists and engineers building fault-tolerant quantum capabilities. In this role, you will make design choices that directly influence production systems, working alongside the FTQC Science Lead to translate research direction into implementable solutions: which error correction approaches to pursue, how to map logical circuits to physical qubits, how to optimize resource usage, and how to integrate decoders into execution flows. You will work at the boundary of science and engineering, where your research directly informs what gets built. This is not a purely theoretical role. You will implement your ideas, benchmark them against real hardware constraints, and iterate with software engineers who translate your designs into scalable infrastructure. We are particularly interested in candidates who have taken QEC research from theory into implementation, whether in simulation or on physical hardware. Key job responsibilities - Drive scientific design decisions for fault-tolerant quantum workloads: error correction code selection, logical gate synthesis, and qubit mapping strategies - Develop and implement resource estimation algorithms that guide compilation optimization - Collaborate with software engineers to translate QEC research into production software - Benchmark approaches against realistic hardware noise models and device constraints - Work with quantum hardware providers on compilation strategies tailored to specific architectures - Publish research in coordination with the broader Braket science team, representing Amazon Braket at relevant conferences and workshops

We are building a agentic intelligence system that transforms unstructured, noisy customer-data into actionable intelligence for product analytics to guide evolution of Amazon Shopping CX's — surfacing metrics on demand and insights unprompted, without an analyst in the loop. We are solving one of the hardest problems in the agent driven data intelligence space to isolate insights from noise. This role will own multi agent system orchestration and context management; self-improving agent layer that gets measurably better over time without human intervention and reliable signal extraction from unstructured data and proactive intelligence that detects what matters before anyone asks. Our agentic system is in production. What we don't yet have is a system that evaluates its own output quality, identifies where it fails, and closes that feedback loop automatically. Key job responsibilities As Senior Data Scientist, you will own the multi agent orchestration and the self-improvement system end-to-end. You will also own designing the overall architecture to extract insights from unstructured data at scale. You will work directly with the principal engineer, influence the technical roadmap across the team, and partner with SDE's. - This role requires operating independently on problems that are not well-defined or structured, identifying and framing research challenges across broad problem areas, and delivering end-to-end solutions that have significant impact on the product. - Own the multi-agent topology (Planner → Worker → Reasoner → Loop Controller) — inter-agent communication protocols, and loop termination logic - Design and manage the context window strategy across agents - Own all system prompts, routing prompts, and chain-of-thought scaffolding across agents - Define what "better" means across dimensions (factual grounding, hypothesis novelty, evidence completeness, reasoning coherence) without ground-truth labels at scale - Design how eval signal propagates back into prompt updates and model routing decisions - Own schema grounding, sparse vector indexing, and domain-scoped kNN queries - Own embedding strategy, intent classification accuracy, and entity extraction quality

The AWS Compliance & Security Assurance Engineering team builds tools and services that scale AWS's ability to exceed security and compliance expectations for our regulators, auditors, and customers globally. We create efficiencies for our teams while maintaining transparency for our customers. As a Data Scientist on our data team, you'll have a unique opportunity to build solutions that scale security assurance capabilities through AI-driven approaches. You'll leverage advanced analytics, machine learning techniques, and state-of-the-art AI technologies on top of highly complex datasets to transform our security assurance operations. You'll also help shape our data science roadmap, fostering data-driven decision-making and delivering significant business impact through innovative methodologies. The ideal candidate brings a strong background in automation by leveraging GenAI Large Language Models (LLMs), combined with experience analyzing complex datasets and a proven ability to transform business needs into deliverables. If you're passionate about applying AI to security challenges in a dynamic environment that offers startup-like autonomy with enterprise impact, we want to hear from you. Key job responsibilities * Analyze and extract hidden insights from complex, large-scale datasets using advanced statistical and AI techniques, using hands-on expertise in data wrangling and manipulation. * Identify high-impact business improvement opportunities, lead the design and execution of data science initiatives to address them. * Apply statistical and ML knowledge to specific business problems and data. * Leverage Vision Language Models (VLMs) and Large Language Models (LLMs) to analyze document/image structure, perform content understanding and metadata extraction. * Rapidly prototype and test AI solutions, while iterating quickly based on data and feedback. * Collaborate cross-functionally to deeply understand business requirements, customer needs, and technical constraints; transforming discovered information into data-driven solutions and actionable recommendations. * Communicate complex technical concepts to technical and non-technical stakeholders; present compelling insights and evidence-based recommendations to leadership. * Stay up-to-date on the latest advancements in AI and identify opportunities to apply emerging techniques to the space. * Collaborate with Business Intelligence, Data Engineers and SDEs to drive the collection of new data and refinement of existing data sources to continually improve data quality. * Actively participate in team design reviews, data modeling discussions, brainstorming activities while mentoring colleagues in state-of-the-art AI tools and methodologies. About the team Diverse Experiences Amazon Security values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why Amazon Security? At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon’s products and services. We offer talented security professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores. Inclusive Team Culture In Amazon Security, it’s in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest security challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices. Training & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, training, and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.

The Sponsored Products and Brands (SPB) team at Amazon Ads is re-imagining the advertising landscape through industry leading 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 are energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. About our team The Sponsored Products and Brands -- Offsite team builds solutions that extend campaigns beyond the Amazon store, reaching shoppers across third-party environments where they discover and shop. We combine large-scale, low-latency systems with advanced machine learning and AI to deliver high-quality sponsored experiences in high-intent surfaces. Key job responsibilities As a Senior Applied Scientist on this team, you will: * Effectively communicate technical and non-technical ideas with teammates and stakeholders, adjusting your delivery to the audience to maximize impact. * Drive or heavily influence the design of scientifically-complex software solutions or systems. You take ownership of these components, providing a system-wide view and design guidance. These systems or solutions can be brand new or evolve from existing ones. * Define a long-term science vision and roadmap for our Offsite advertising business, driven from our customers' needs. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. * Work closely with engineers and product managers to design, implement and launch AI solutions end-to-end. * Design and conduct A/B experiments to evaluate proposed solutions based on in-depth data analyses. * Identify opportunities where GenAI solutions can accelerate learning and efficiency, and drive greater advertiser outcomes. * Mentor and guide junior scientists, fostering a collaborative and high-performing team culture. * Stay up-to-date with advancements and the latest modeling techniques in the field

Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video technologist, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! Prime Video is disrupting traditional media with an ever-increasing selection of movies, TV shows, Emmy Award-winning original content, add-on subscriptions, and live events like Thursday Night Football. Within this expanding ecosystem, Linear TV with its 24/7 scheduled broadcast-style programming has emerged as one of our fastest-growing segments, with viewership hours increasing significantly year over year. This growth demonstrates that even in the streaming era, customers deeply value the lean-back, curated experience that Linear TV provides. Key job responsibilities As an Applied Scientist on LPEX, you will be a technical owner and science leader across the following areas: * Define and drive the science strategy and multi-year roadmap for Linear TV personalization, translating research advances into measurable business and customer experience outcomes. * Design, develop, and deploy machine learning models for content recommendation, viewer engagement optimization, and real-time personalization at the scale of hundreds of millions of Prime Video customers. * Own the complete ML lifecycle: problem formulation, data analysis, feature engineering, model development, offline and online evaluation, and reliable production deployment. * Build and continuously optimize recommendation systems with strict real-time latency requirements, ensuring that personalization decisions are delivered at speed and scale. * Design and execute rigorous A/B and multivariate experiments to measure recommendation quality, understand causal drivers of engagement, and iterate rapidly toward customer impact. * Partner with software engineering teams to productionize ML models, defining requirements for serving infrastructure, data pipelines, and model monitoring and observability. * Collaborate with product managers and cross-functional stakeholders to translate ambiguous business problems into well-scoped, tractable science solutions. * Publish research findings and contribute to the broader scientific community through papers, patents, and internal knowledge-sharing forums. * Mentor scientists and engineers on the team, setting a high bar for scientific rigor, experimental discipline, and ML engineering best practices. A day in the life We are looking for an Applied Scientist who will define and drive the science strategy for personalization and recommendations on Linear TV. You will own the end-to-end machine learning lifecycle from problem formulation and research through experimentation and production deployment, building systems that help millions of customers discover the right content at the right time. It's Day 1 for personalizing the linear TV experience on Prime Video, and you will be at the forefront of this innovation. About the team The Linear Personalization Experience (LPEX) team is building next-generation, AI-powered personalization and recommendation systems to enhance this natural engagement and deliver a best-in-class Linear TV experience for Prime Video customers worldwide. The LPEX team's vision is to surface the breadth and depth of Prime Video's linear selection at exactly the right moment for each customer curating the most relevant programming, tailored to individual tastes, purchase behaviors, schedules, and viewing habits, while simultaneously elevating awareness of our extensive live and linear catalog. Our mission is to anticipate and exceed viewers' expectations, fostering deeper connections with the content they love. We adapt to viewers' preferences and propensities for both live and on-demand viewing, enriching the overall entertainment journey. The team operates at the intersection of machine learning research, large-scale distributed systems, and consumer product strategy, partnering closely with product management, engineering, and business development.

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 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 - 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.

Are you a scientist interested in pushing the state of the art in machine learning and recommendation systems? Are you interested in working on novel ideas that can positively impact millions of customers? Do you wish you had access to large datasets and tremendous computational resources? Answer yes to any of these questions and you will be a great fit for our team at Amazon. Our team is part of Amazon’s Personalization organization, a high-performing group that leverages Amazon’s expertise in machine learning, big data, distributed systems, and user experience design to deliver the best shopping experiences for our customers. Our team builds large-scale machine-learning solutions that delight customers with personzlized content recommendations, at the right time, with the right level of explanation. As an Applied Scientist in our team, you will be responsible for the research, design, and development of new AI technologies for personalization. You will adopt or invent new machine learning and analytical techniques in the realm of recommendations and large language models. You will collaborate with scientists, engineers, and product partners locally and abroad. Your work will include inventing, experimenting with, and launching new features, products and systems. Please visit https://www.amazon.science for more information.

Are you passionate about applying machine learning, time series forecasting, and operations research to transform the delivery of heavy and bulky items for Amazon customers? Are you excited about working with large-scale operational data and developing models that drive real business impact? If so, the Amazon Extra Large (AMXL) Science team may be the right fit for you. AMXL is Amazon's specialized business for delivering heavy and bulky items — appliances, furniture, fitness equipment, and mattresses — with a premium customer experience that includes room-of-choice delivery, at-home installations, and assembly services. In this role, you will leverage large-scale operational data to develop and deploy predictive models and optimization solutions that solve real-world logistics and fulfillment challenges, partnering closely with scientists, engineers, and business stakeholders. Key job responsibilities Apply machine learning, statistical modeling, time series analysis, and operations research techniques to build solutions for delivery routing, capacity planning, demand forecasting, workforce scheduling, and network optimization Analyze large-scale historical and real-time operational data to surface efficiency patterns, bottlenecks, and emerging trends across the AMXL network Develop, validate, and deploy models that improve cost-to-serve and customer experience Partner with cross-functional teams to implement data-driven strategies and measure impact Build scalable, automated pipelines for data ingestion, feature engineering, model training, and validation Monitor deployed model performance and communicate results through clear reporting on key operational and business metrics A day in the life You'll be part of a small, collaborative team of scientists who move fast and care deeply about the problems they solve. A typical week might involve whiteboarding a new forecasting approach with a senior scientist, partnering with engineers to push a model into production, deep-diving into operational data to understand why a metric moved, or presenting your findings to business leaders who will act on them. The work is high-visibility and high-impact. The models you build will directly influence how millions of heavy and bulky items reach customers. About the team The AMXL Science team is a worldwide group of data scientists, applied scientists, and product managers solving Amazon's most complex heavy bulky supply chain challenges. We build forecasting models, capacity planning systems, and optimization tools that directly impact millions of customer deliveries. Our culture values scientific rigor, measurable business impact, and clear communication. We start with baselines, earn complexity, and partner closely with operations to ensure our work drives real decisions. You'll tackle problems where logistics constraints demand creative, data-driven solutions — and see your models shape labor planning, routing, and customer experience at scale.