Careers

We are seeking an Applied Scientist to help build Amazon’s next-generation customer memory and personalization systems. Are you interested in building systems that move beyond reacting to customer behavior, to actually understanding and remembering it over time? Our team is building Amazon’s customer memory layer – a system that extracts, curates, and reasons over customer knowledge to power next-generation personalization. This includes transforming noisy, unstructured signals into durable, high-quality representations of customer preferences, intents, and life events, and using them in real time to improve customer experiences. We are part of Amazon’s Personalization organization, a high-performing group that leverages large-scale machine learning, generative AI, and distributed systems to deliver highly relevant customer experiences. We tackle challenging problems at the intersection of information extraction, knowledge representation, LLM reasoning, and recommendation systems. Our systems operate under real-world constraints of scale, latency, and quality, requiring careful tradeoffs between precision, recall, and responsiveness. This team plays a central role in defining how Amazon understands its customers, and how that understanding is applied across the shopping experience. As an Applied Scientist, you will design and build ML and LLM-powered solutions for Amazon's customer memory and personalization systems. You will work on how customer knowledge is extracted, validated, and applied in production systems. You will own the end-to-end delivery of ML solutions, from problem formulation and modeling to offline and online experimentation, and production deployment at scale. You will deliver high-quality, scalable systems that power customer-facing experiences. You will drive work across areas such as fact extraction, memory quality and lifecycle, temporal reasoning, and grounded personalization, while navigating tradeoffs between quality, latency, and coverage. You will collaborate closely with engineering and product teams to translate research into measurable customer impact. Please visit https://www.amazon.science for more information.

We are seeking an Applied Scientist to help build Amazon’s next-generation customer memory and personalization systems. Are you interested in building systems that move beyond reacting to customer behavior, to actually understanding and remembering it over time? Our team is building Amazon’s customer memory layer – a system that extracts, curates, and reasons over customer knowledge to power next-generation personalization. This includes transforming noisy, unstructured signals into durable, high-quality representations of customer preferences, intents, and life events, and using them in real time to improve customer experiences. We are part of Amazon’s Personalization organization, a high-performing group that leverages large-scale machine learning, generative AI, and distributed systems to deliver highly relevant customer experiences. We tackle challenging problems at the intersection of information extraction, knowledge representation, LLM reasoning, and recommendation systems. Our systems operate under real-world constraints of scale, latency, and quality, requiring careful tradeoffs between precision, recall, and responsiveness. This team plays a central role in defining how Amazon understands its customers, and how that understanding is applied across the shopping experience. As an Applied Scientist, you will design and build ML and LLM-powered solutions for Amazon's customer memory and personalization systems. You will work on how customer knowledge is extracted, validated, and applied in production systems. You will own the end-to-end delivery of ML solutions, from problem formulation and modeling to offline and online experimentation, and production deployment at scale. You will deliver high-quality, scalable systems that power customer-facing experiences. You will drive work across areas such as fact extraction, memory quality and lifecycle, temporal reasoning, and grounded personalization, while navigating tradeoffs between quality, latency, and coverage. You will collaborate closely with engineering and product teams to translate research into measurable customer impact. Please visit https://www.amazon.science for more information.

Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video subscriptions such as Apple TV+, HBO Max, Peacock, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video team member, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! The Prime Video Ads - Growth, Engagement and monetization (GEM) team is responsible for deciding for every stream, every break, every impression what the right ad experience is for the customer and the right price for the advertiser. We own the centralized decisioning layer, the situation-aware ad load system, the ML prediction platform, the long-term measurement framework, and the experimentation platform that gates every change to production. We are hiring a customer-focused, solutions-oriented Data Scientist to build and guide data-driven frameworks that determine which personalization, yield, and supply innovations are working for customers, advertisers, and the business. You will be embedded on projects that are fast-paced, challenging, and directly influence what hundreds of millions of customers see when they watch Prime Video. Key job responsibilities - Use advanced statistical and machine learning techniques to extract insights from large-scale streaming, ad delivery, and auction data sets. - Design and implement end-to-end data science workflows from data acquisition and cleaning through model development, offline evaluation, A/B testing, and production deployment in partnership with product and engineering teams - Build, validate, and maintain the statistical models that support the roadmap including Supply tier classification and Supply Quality Index, ad tolerance and fatigue scoring, and propensity and disengagement prediction - Partner with product and economist teams to design hold out experiments to measure impact of Ad load on revenue and customer engagement; define north star metrics, power calculations, holdout structures, and promotion gates for every major lever. - Support scalable, self-service analytics by building curated datasets for PVa product, ops, sales, and science covering supply, yield, CX, and advertiser diversification outcomes. - Partner with product stakeholders and science peers to identify strategic, data-driven opportunities to improve the customer experience and advertiser results. - Communicate findings, conclusions, and recommendations to technical and non-technical stakeholders - Stay up-to-date on the latest data science tools, techniques, and best practices and help evangelize them across the organization

Join Amazon's Frontier AI & Robotics team as a Member of Technical Staff, this Technical Program Manager will become the driving force behind breakthrough robotics innovation. You'll orchestrate complex, cross-functional programs that bridge AI research, software, hardware, and production deployment—managing the technical workstreams that enable robots to see, reason, and act in Amazon's warehouse environments. Your program leadership will directly accelerate our mission to build the next generation of embodied intelligence. Key job responsibilities · Establish and drive program management mechanisms and cadence for complex robotics and AI development initiatives spanning research, software engineering, hardware, and operations · Manage end-to-end program execution across the full robotics stack—including AI models, software engineering, and hardware deployment · Drive decision-making velocity by facilitating tradeoff discussions when there are conflicting priorities; determine whether decisions are one-way or two-way doors · Own program-level risk management, proactively identifying technical, schedule, and resource risks; escalate where necessary and drive mitigation strategies · Manage dependencies and scope changes across internal teams and partner organizations, ensuring alignment on commitments, timelines, and technical requirements · Create transparency through clear RACI frameworks, program dashboards, and communication mechanisms that keep stakeholders aligned on status, risks, and decisions · Exercise strong technical judgment to influence program-level decisions on deployment methodology, scalability requirements, and technical feasibility—acting as the voice back to research and engineering teams · Build sustainable program management processes that scale as our organization grows, adapting agile frameworks to the unique challenges of AI robotics A day in the life Your focus centers on driving velocity and alignment across our robotics programs. You might start your morning facilitating tradeoff decisions between AI researchers and software engineers on a critical prototype milestone, then transition to managing dependencies across hardware and operations teams to keep timelines on track. In the afternoon, you could be conducting risk assessments on supply chain constraints that impact our development roadmap, updating program dashboards to provide leadership visibility, or working with partner teams to align on deployment strategies. You'll establish the mechanisms and cadence that keep our fast-moving organization synchronized—from sprint planning rituals to cross-functional design reviews. Throughout the day, you balance hands-on program execution with strategic escalation, ensuring technical decisions align with our long-term vision while removing obstacles that slow teams down. You're the connective tissue that enables researchers, engineers, and operations specialists to move fast together. About the team At Frontier AI & Robotics, we're not just advancing robotics – we're reimagining it from the ground up. Our team is building the future of intelligent robotics through frontier foundation models and end-to-end learned systems. We tackle some of the most challenging problems in AI and robotics, from developing sophisticated perception systems to creating adaptive manipulation strategies that work in complex, real-world scenarios. What sets us apart is our unique combination of ambitious research vision and practical impact. We leverage Amazon's computational infrastructure and rich real-world datasets to train and deploy state-of-the-art foundation models. Our work spans the full spectrum of robotics intelligence – from multimodal perception using images, videos, and sensor data, to sophisticated manipulation strategies that can handle diverse real-world scenarios. We're building systems that don't just work in the lab, but scale to meet the demands of Amazon's global operations. Join us if you're excited about pushing the boundaries of what's possible in robotics, working with world-class researchers, and seeing your innovations deployed at unprecedented scale.

We are seeking to hire software engineers who are excited about research for robot manipulation with the goal of developing manipulation systems at human-level performance. Our strategy focuses on a real2sim2real pipeline that learns from large scale human videos and leverage simulation and reinforcement learning to bridge the human-to-robot embodiment gap. Key job responsibilities • Learning manipulation: Design and implement robot learning algorithms for manipulation • Leverage vision models to extract 3D hand-object manipulation information from real-world situations • Develop large-scale real2sim2real pipeline for manipulation • Multimodal Sensor Fusion: Integrate tactile sensing, proprioception and vision into the learning pipeline 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.

We are seeking an Applied Scientist to develop and optimize Visual Inertial Odometry (VIO) and sensor fusion systems for our intelligent robots. In this role, you will design, implement, and deploy state estimation and tracking algorithms that enable robots to understand their position and motion in real time, even in challenging and dynamic environments. You will own the full pipeline from algorithm development through embedded deployment, ensuring that perception systems run efficiently on resource-constrained robotic hardware. You will also leverage modern machine learning approaches to push the boundaries of classical perception methods, combining learned representations with geometric techniques to achieve robust, real-time performance. This is a deeply hands-on role. You will work directly with sensors, hardware, and real-world data, while prototyping, testing, and iterating in physical environments. The ideal candidate has strong foundations in VIO and sensor fusion, practical experience optimizing algorithms for embedded platforms, and familiarity with how modern deep learning is transforming perception. Key job responsibilities - Design and implement Visual Inertial Odometry algorithms for robust real-time state estimation on robotic platforms like Sprout - Develop multi-sensor fusion pipelines integrating cameras, IMUs, and other sensing modalities for accurate pose tracking - Optimize perception and tracking algorithms for deployment on embedded hardware (e.g., ARM, GPU-accelerated edge devices) under strict latency and power constraints - Apply modern ML-based perception techniques (learned features, depth estimation, neural odometry) to complement and improve classical geometric approaches - Build and maintain calibration, evaluation, and benchmarking infrastructure for perception systems - Collaborate with hardware, controls, and navigation teams to integrate perception outputs into the robot’s autonomy stack - Lead technical projects from research prototyping through production deployment

We are seeking a hands-on Electrical Engineer to lead the design and integration of electrical systems or subsystems for high-degree-of-freedom robotic platforms. This role involves architecting the robot’s power distribution, sensor wiring, and embedded electrical infrastructure. You will be responsible for designing across the full electrical system for advanced robotics platforms including power distribution, sensing, compute, motor controllers, communication infrastructure, battery system and power electronics in close collaboration with mechanical, controls and software engineers. You’ll play a key role in ensuring high-performance, reliable operation of complex electromechanical systems under real-world conditions. Key job responsibilities * Electrical system architect / owner for power electronics, actuation, PCBAs, battery, ware harness specs and high speed electrical/communications protocols * Design, develop and integrate power distribution, embedded electronics, motor controllers and safety-critical circuits for complex robotic systems * Own board layout of PCBAs including SoCs, microcontrollers, sensors, power devices, etc. using Cadence OrCAD/Allegro or equivalent tools. Oversee bring-up and validation * Determine appropriate high speed electrical and communication protocols (e.g., CAN, EtherCAT, USB, etc) for reliable and efficient system operation * Specify and design custom power electronics and power distribution boards to meet performance, thermal, and safety requirements * Design and route all cabling and wire harnesses across the robotic platform, considering EMI, signal integrity, serviceability, and integration with mechanical structures * Architect and integrate the robot’s battery system, including protection circuitry, battery management, charging systems, and thermal considerations * Define and implement wiring and electrical interfaces for sensors (e.g., lidar, stereo cameras, IMUs, tactile) and compute modules * Ownership over prototyping and bringing up electrical designs and creation of test & validation rigs About the team At Frontier AI & Robotics, we're not just advancing robotics – we're reimagining it from the ground up. Our team is building the future of intelligent robotics through innovative 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.

We're seeking talented Robotics Software Engineers to expand our software team. This highly technical role involves designing, implementing, and optimizing software solutions across diverse AI robotics hardware that support both autonomous, teleoperation, and ML training/evaluation. You'll work closely and collaboratively with multidisciplinary teams; including software, hardware, research, and operations - to drive advancements in our robotic systems. Key job responsibilities • Work with mechanical, control, EE, and ML engineering teams to bring up and integrate sensors and actuators • Design and build software framework to accelerate development of full robotics applications • Work with AI researchers to build inferencing, training, and evaluation software for robotics controls. • Create testing environment for HW/SW/Policy testing and QA About the team At Frontier AI & Robotics, we're not just advancing robotics – we're reimagining it from the ground up. Our team is building the future of intelligent robotics through frontier foundation models and end-to-end learned systems. We tackle some of the most challenging problems in AI and robotics, from developing sophisticated perception systems to creating adaptive manipulation strategies that work in complex, real-world scenarios. What sets us apart is our unique combination of ambitious research vision and practical impact. We leverage Amazon's 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+ is the world’s best Generative AI powered personal assistant / agent for consumers. We are seeking an Applied Scientist to join our newly expanding team in India focused on Alexa Conversational Ads and Personalization. In this role, you will build machine learning models that seamlessly and naturally integrate relevant advertising into the Alexa experience while deeply personalizing user interactions. You will work closely with other scientists, engineers, and product managers to take models from conception to production. Key job responsibilities - Design, develop, and evaluate innovative machine learning and deep learning models for natural language processing (NLP), recommendation systems, and personalization. - Conduct hands-on data analysis and build scalable ML pipelines. - Design and run A/B experiments to measure the impact of new models on customer experience and ad performance. - Collaborate with software development engineers to deploy models into high-scale, real-time production environments.

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 About the team 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.