Careers

Help us build the software stack underneath Frontier AI & Robotics: the layer between hardware and the AI policies running on it. You’ll work end-to-end across the stack, from bringing up sensors and actuators at the HW/SW boundary, to hardening the multi-process runtime that ties them together, to shipping the framework changes that let the rest of the team move faster. This is a generalist role with a real systems edge. We need someone equally at home down at the sensor and OS boundary (drivers, IPC, real-time behavior, profiling) and up in robotics application code (most of it Python). You’ll spend stretches of a few days to a few weeks each on things like bringing up a new sensor at the protocol layer, chasing a flaky USB camera at the kernel boundary, generalizing the camera stack, cutting perception latency, porting code onto edge compute, or chasing a DDS/ROS 2 performance regression. You’ll work with sharp, motivated engineers across hardware, ML research, controls, and ops on continuously changing problems at the frontier of AI and robotics. The role rewards engineers who communicate clearly, invest in cross-team relationships, and ship. Key job responsibilities - Bring up and integrate sensors, actuators, and edge compute across diverse robotics hardware platforms. - Build and improve the multi-process Python and ROS 2 runtime: process management, IPC, observability, lifecycle. - Diagnose and fix bottlenecks across the stack: middleware performance (DDS, ROS 2), perception pipeline latency, edge inference throughput, system-level resource contention. - Generalize one-off solutions into reusable infrastructure (camera stacks, telemetry pipelines, edge deployment tooling) that scales across hardware platforms and use cases. - Port code onto the constrained edge-compute platforms our robots run. Make it work, then make it work well. - Identify gaps in the team’s velocity, whether that’s a missing piece of infrastructure or a fragile sensor that nobody has time to fix, and close them. - Make proper tradeoffs between prototyping and production software. 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.

Do you have a passion for GenAI, machine learning, and/or cybersecurity?! If so, join us in building innovative AI/ML services that protect our cloud from advanced security threats! As a Senior Applied Scientist on our team, you’ll analyze data using GenAI and other AI/ML techniques to build new services that detect and automate the mitigation of cybersecurity threats across Amazon’s infrastructure, including advanced persistent threats. You’ll work with software development engineers, security engineers, and other applied scientists across multiple teams to develop innovative security solutions at a massive scale. Our services protect the AWS cloud for all customers, helping preserve our customers’ trust in us. You’ll get to use the full power and breadth of AWS technologies to build services that proactively protect every single AWS customer, both internally and externally, from security threats – not many teams can say that! A successful candidate is one who is passionate about utilizing big data, machine learning, and GenAI to solve real business problems. This role gives you the opportunity to lead technical innovation and drive the future direction of automation within threat detection and mitigation. Candidates are expected to have a track record of delivering high-quality results in a fast-moving environment. We need someone who’s comfortable mentoring, leading by example, and independently delivering. We have a team culture that encourages innovation and for every team member to have a high degree of ownership for their program, vision, and execution of ideas. We’re looking for someone who is enthusiastic, empathetic, curious, motivated, reliable, and able to work effectively with a diverse team of peers and partner teams. We want someone who will help us amplify the positive and inclusive team culture we’ve been building. Key job responsibilities - Design, build, and deploy AI/ML systems that process threat data at scale, running over petabyte-scale security logs with real-time inference - Conduct thorough data analyses and develop prototypes for detecting otherwise-unknown security problems - Independently frame ambiguous problems, and then define and deliver a research agenda with limited guidance - Seek out, develop, and advocate for new technologies to solve scientifically-complex security problems - Build consensus on scientific approaches, balancing analytic rigor with the operational urgency inherent to security - Mentor and develop teammates both technically and professionally - Publish patents and peer-reviewed articles, and present your research both internally and externally About the team This team is part of the larger ‘Amazon Active Defense’ organization, focused on bringing automation – at scale – to AWS Security. Teams within Amazon Active Defense consist of security engineers, data/applied scientists, and software developers, all working together to launch big data analytics able to automatically detect and mitigate threats within AWS in near-real-time. This team, in particular, is focused on both detecting and automatically stopping advanced actor activities in internal AWS resources. Review these blogs for example past projects you could have led! - https://aws.amazon.com/blogs/security/how-aws-uses-active-defense-to-help-protect-customers-from-security-threats/ - https://www.amazon.science/blog/how-amazon-uses-agentic-ai-for-vulnerability-detection-at-global-scale - https://www.amazon.science/blog/how-amazon-uses-ai-agents-to-anticipate-and-counter-cyber-threats 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 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.

Are you driven by the challenge of solving complex problems that directly impact the safety and well-being of millions of Amazon Associates worldwide? Do you want to push the boundaries of artificial intelligence (AI) to build advanced solutions that make workplaces safer and more efficient? If so, we invite you to join our WHS Data-Tech team as a Senior Applied Scientist and take your career to the next level. At WHS Data-Tech, we leverage computer vision (CV), large language models (LLMs), and AI-driven innovations to develop industry-leading solutions that proactively enhance workplace safety. Our work spans real-time risk assessment, analytics, and AI-powered insights, all aimed at creating a safer work environment at scale. As a Senior Applied Scientist specializing in CV and LLMs, you will play a pivotal role in shaping our next-generation safety solutions. You’ll lead the innovation, design and implementation of AI-powered features that redefine workplace safety. Your work will drive strategic decisions, optimize system architecture, and influence best practices, ensuring our technology remains pioneering. If you are not sure that every qualification listed describes you perfectly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skill-sets. If you’re passionate about this role and want to make an impact on a global scale, please apply! Key job responsibilities • Invent and apply novel CV and LLM approaches to analyze complex, multimodal data. Distinguish problems that require fundamentally new solutions from those addressable through existing methods. • Architect and implement core scientific components of CV and LLM-based solutions. Deploy scalable, production-grade models across on-device and cloud environments in collaboration with engineering teams. • Design evaluation frameworks and conduct rigorous experiments. Benchmark against state-of-the-art and iterate on model architectures to advance performance. • Stay at the forefront of computer vision, LLMs, and generative AI research. Proactively identify and prototype novel techniques for integration into production solutions. • Collaborate with product managers, program managers, and business stakeholders to translate ambiguous problems into well-scoped ML solutions with measurable impact. • Build consensus on complex projects and decompose them into independent workstreams. Identify and resolve technical bottlenecks that limit innovation. • Propose research initiatives, secure leadership alignment, and present technical trade-offs and strategic recommendations to stakeholders. • Author internal technical documents and research papers. Contribute to the scientific community through conferences and peer reviews. • Actively mentor team members, elevating scientific capabilities and fostering a culture of innovation and rigorous inquiry. About the team WHS Data-Tech's charter is to deliver technology solutions and data insights that help reduce workplace risks and injuries at Amazon. Our customers are Worldwide (WW) Operations and the WHS organization. The technology solutions landscape for WHS Data-Tech includes applications built using native Amazon Web Services (AWS) technologies and device-software hybrid solutions that leverage generative artificial intelligence (AI), computer vision, sensors, and Internet of Things (IoT) technologies. The team also conducts scientific research and modeling to generate safety insights, and provides analytical solutions ranging from senior leadership deliverables to business-unit-specific reports.

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. At Amazon, you'll work alongside the latest AI and GenAI tools that are increasingly woven into how teams operate: from AI-powered capabilities that accelerate decision-making, to Generative AI that helps you focus on work that truly matters. You'll have opportunities and resources to develop AI fluency at your own pace, with continuous learning built into the culture. 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.

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! We are looking for a self-motivated, passionate and resourceful Applied Science Manager to bring diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. You will lead a strong science team and work closely with other science and engineering leaders, product and business partners together to build the best personalized customer experience for Prime Video. At the end of the day, you will have the reward of seeing your contributions benefit millions of Amazon.com customers worldwide. Key job responsibilities - Lead to develop AI solutions for various Prime Video recommendation and personalization systems using Deep learning, GenAI, Reinforcement Learning, recommendation system and optimization methods; - Work closely with engineers and product managers to design, implement and launch AI solutions end-to-end; - Effectively communicate technical and non-technical ideas with teammates and stakeholders; - Stay up-to-date with advancements and the latest modeling techniques in the field; - Hire and grow a science team working in this exciting video personalization domain. About the team Prime Video Recommendation Science team owns science solution to power recommendation and personalization experience on various devices. We work closely with the engineering teams to launch our solutions in production.

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.

The Alexa Edge AI team is seeking a talented and motivated Applied Scientist to join our newly established team in Bangalore. In this role, you will design, develop, and deploy state-of-the-art machine learning models spanning computer vision (CV), audio (including speech) processing, and multimodal semantic understanding for both edge and cloud deployment. You will work at the intersection of multiple modalities to build systems that can perceive, interpret, and reason about the world — pushing the boundaries of what's possible in unified multimodal intelligence. This is a unique opportunity to be a founding member of a brand-new site, shaping the team culture, technical direction, and research agenda from the ground up. Key job responsibilities Model Development: Design and build deep learning models for computer vision, audio understanding, and multimodal semantic fusion — including architectures that enable joint reasoning across visual, auditory, and textual modalities. End-to-End Ownership: Own the full ML lifecycle — from problem formulation, data strategy, and annotation design through experimentation, evaluation frameworks, model optimization, and deployment at scale. Research & Innovation: Stay at the frontier of CV, audio ML, and multimodal learning; identify and apply cutting-edge techniques and contribute to the scientific community through papers at top-tier venues (CVPR, NeurIPS, ICASSP, ICCV, ACL). Mentorship & Culture Building: As a founding member of the Bangalore site, help hire, onboard, and establish the technical practices that define the team's culture. A day in the life An Applied Scientist with the Alexa Edge AI team will support science solution design, run experiments, research new algorithms, and find new ways of optimizing the customer experience; while setting examples for the team on good science practice and standards. Besides theoretical analysis and innovation, an Applied Scientist will also work closely with talented engineers and scientists to put algorithms and models into production. About the team The Alexa Edge AI team has a mission to deliver best in class, resource efficient multimodal AI models in support of various perception (vision, audio and speech) and semantic understanding based applications for devices like Echo Show series within Amazon.

The Alexa Edge AI team is seeking a talented and motivated Applied Scientist to join our newly established team in Bangalore. In this role, you will design, develop, and deploy state-of-the-art machine learning models spanning computer vision (CV), audio (including speech) processing, and multimodal semantic understanding for both edge and cloud deployment. You will work at the intersection of multiple modalities to build systems that can perceive, interpret, and reason about the world — pushing the boundaries of what's possible in unified multimodal intelligence. This is a unique opportunity to be a founding member of a brand-new site, shaping the team culture, technical direction, and research agenda from the ground up. Key job responsibilities Model Development: Design and build deep learning models for computer vision, audio understanding, and multimodal semantic fusion — including architectures that enable joint reasoning across visual, auditory, and textual modalities. End-to-End Ownership: Own the full ML lifecycle — from problem formulation, data strategy, and annotation design through experimentation, evaluation frameworks, model optimization, and deployment at scale. Research & Innovation: Stay at the frontier of CV, audio ML, and multimodal learning; identify and apply SOTA techniques and contribute to the scientific community through papers at top-tier venues (CVPR, NeurIPS, ICASSP, ICCV, ACL). Mentorship & Culture Building: As a founding member of the Bangalore site, help hire, onboard, and establish the technical practices that define the team's culture. A day in the life An Applied Scientist with the Alexa Edge AI team will support science solution design, run experiments, research new algorithms, and find new ways of optimizing the customer experience; while setting examples for the team on good science practice and standards. Besides theoretical analysis and innovation, an Applied Scientist will also work closely with talented engineers and scientists to put algorithms and models into production. About the team The Alexa Edge AI team has a mission to deliver best in class, resource efficient multimodal AI models in support of various perception (vision, audio and speech) and semantic understanding based applications for devices like Echo Show series within Amazon.