Careers

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.

We are looking for a Senior Applied Scientist to help establish and lead the technical direction of our newly formed team in Bangalore. In this role, you will drive the research and development of next-generation machine learning models spanning computer vision, audio processing, and multimodal semantic understanding. You will help define the science roadmap, tackle high-ambiguity problems across modalities, and deliver solutions that operate at scale. This is a rare opportunity to shape the technical vision, culture, and long-term research agenda of a greenfield site. Key job responsibilities Model Development & Technical Leadership: Architect and drive development of advanced deep learning models for CV, audio understanding, and multimodal semantic fusion — setting the technical bar and defining best practices for the team. End-to-End Ownership: Own complex ML programs end-to-end — from identifying high-impact problems, designing data strategies and evaluation frameworks, through experimentation, optimization, and deployment at production scale. Research & Innovation: Define the science roadmap for your area; drive novel research directions in multimodal learning and deliver results that advance both the product and the broader field. Publications & Thought Leadership: Maintain an active publication record at top-tier venues (e.g. CVPR, NeurIPS, ICASSP, ICCV, ACL) and represent the team externally in the research community. Mentorship & Culture Building: Mentor scientists and engineers, raise the technical bar through hiring, and play a foundational role in establishing the Bangalore site's culture, processes, and scientific identity. A day in the life An Applied Scientist with the Alexa Edge AI team will lead 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, a Sr. Applied Scientist will also drive cross functional collaboration 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.

Amazon’s Frontier AI & Robotics (FAR) team is seeking a Member of Technical Staff, Infrastructure to build and scale the foundational systems that power our robotics research and development platform. In this role, you will design and operate the distributed infrastructure that enables our researchers and engineers to train foundation models, run large-scale experiments, and deploy intelligent robotic systems at Amazon scale. Join the next revolution in robotics, where you’ll work alongside world-renowned AI pioneers to push the boundaries of what’s possible in robotic intelligence. As a Member of Technical Staff focused on Infrastructure, you’ll build the critical platform layer that accelerates every aspect of FAR’s research — from high-throughput data pipelines and experiment management systems to low-latency model serving and configuration delivery for robotic deployments. This role is deeply technical and focuses on performance, scalability, and reliability at scale. You will design systems that support volumes of training data, operate with strict latency requirements, and provide the compute and data foundation that enables breakthrough research across FAR’s robotics ecosystem. Key job responsibilities • Design and build scalable compute and data infrastructure to support model training, inferencing, and eval for frontier AI/Robotics development • Lead large technical initiatives and shape the architecture of FAR’s research platform infrastructure • Develop tooling and frameworks that accelerate research workflows, including dataset management, visualization, and quality assessment systems • Optimize query performance and data availability for experimentation and analytics workflows used by research teams • Improve the performance, efficiency, and reliability of FAR’s core compute and storage infrastructure, ensuring systems remain fast and stable at scales • Build highly scalable experimentation and analytics infrastructure to support model evaluation, A/B testing, and feature performance • Collaborate directly with science and robotics teams to support research projects through both infrastructure development and hands-on technical contribution

The Alexa International Tech (AIT) team is looking for a passionate, talented, and inventive Applied Scientist with a strong deep learning background, to build industry-leading Generative Artificial Intelligence (GenAI) technology with Large Language Models (LLMs) and multimodal systems. As part of this team, you will have the opportunity to work on Niche technology that powers Alexa for hundreds of millions of customers worldwide. You will push the boundaries of what's possible with generative AI, developing novel approaches to make Alexa sound more natural, expressive, and culturally relevant across multiple languages and locales. This is a unique opportunity to combine fundamental research with large-scale production impact, working at the intersection of speech synthesis, large language models, and multimodal AI systems. Key job responsibilities As an Applied Scientist in the Alexa International Tech team within Alexa AI, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art in multi-modal models, with a focus on speech generation. You will leverage Amazon's heterogeneous data sources and large-scale computing resources to build machine learning models that deliver natural, expressive, and culturally appropriate speech experiences across multiple languages. You will design and conduct experiments, prototype new approaches, and iterate rapidly to validate hypotheses. You will publish your findings at top-tier conferences and contribute to Amazon's intellectual property portfolio. You will collaborate closely with engineering teams to transition research prototypes into production systems that serve customers at scale. This role requires a pragmatic technical leader comfortable with ambiguity, capable of summarizing complex data and models through clear visual and written explanations. You will mentor junior scientists, influence technical direction, and communicate results effectively to both technical and non-technical stakeholders. 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 is a global team with engineering teams in all 3 regions. Our vision is to build an Alexa assistant that is culturally relevant, linguistically fluent, and locally present. Our team operates with a startup mentality within Amazon, moving fast to deliver breakthrough experiences while maintaining the highest scientific rigor.

As part of the AWS Solutions organization, we have a vision to provide business applications, leveraging Amazon’s unique experience and expertise, that are used by millions of companies worldwide to manage day-to-day operations. We will accomplish this by accelerating our customers’ businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. We blend vision with curiosity and Amazon’s real-world experience to build opinionated, turnkey solutions. Where customers prefer to buy over build, we become their trusted partner with solutions that are no-brainers to buy and easy to use. Key job responsibilities Everyone on the team needs to be entrepreneurial, wear many hats and work in a highly collaborative environment that’s more startup than big company. We’ll need to tackle problems that span a variety of domains: computer vision, image recognition, machine learning, real-time and distributed systems. As a Sr. Applied Scientist, you will help solve a variety of technical challenges and mentor other scientists. You will be the thought leader of the team. You will tackle challenging, novel situations every day and given the size of this initiative, you’ll have the opportunity to work with multiple technical teams at Amazon in different locations. You should be comfortable with a degree of ambiguity that’s higher than most projects and relish the idea of solving problems that, frankly, haven’t been solved at scale before - anywhere. Along the way, we guarantee that you’ll learn a ton, have fun and make a positive impact on millions of people. A key focus of this role will be developing and implementing advanced visual reasoning systems that can understand complex spatial relationships and object interactions in real-time. You'll work on designing autonomous AI agents that can make intelligent decisions based on visual inputs, understand customer behavior patterns, and adapt to dynamic retail environments. This includes developing systems that can perform complex scene understanding, reason about object permanence, and predict customer intentions through visual cues. About the team Just Walk Out (JWO) is a new kind of store with no lines and no checkout—you just grab and go! Customers simply use the Amazon Go app to enter the store, take what they want from our selection of fresh, delicious meals and grocery essentials, and go! Our checkout-free shopping experience is made possible by our Just Walk Out Technology, which automatically detects when products are taken from or returned to the shelves and keeps track of them in a virtual cart. When you’re done shopping, you can just leave the store. Shortly after, we’ll charge your account and send you a receipt. Check it out at amazon.com/go. Designed and custom-built by Amazonians, our Just Walk Out Technology uses a variety of technologies including computer vision, sensor fusion, and advanced machine learning. Innovation is part of our DNA! Our goal is to be Earths’ most customer centric company and we are just getting started. We need people who want to join an ambitious program that continues to push the state of the art in computer vision, machine learning, distributed systems and hardware design.

The North America Stores GenAI Evaluation Media (GEM) team is seeking an Applied Scientist to help shape the future of visual shopping experiences. We're building CXs and foundational capabilities to understand, enhance, and generate real-time GenAI imagery, videos and CXs that inspire customers and drive purchase confidence, towards our vision to be the leader in visual media. Specifically, the charter will focus on visual agentic experiences, multi-modal personalization, and real-time image/video generation, looking ahead as customer shopping continues to inspirational assistant-driven experiences. As an Applied Scientist on the team, you will drive the research and development of agentic AI capabilities that inform and guide the customer's shopping journey through visuals. This includes building core science primitives for multimodal understanding, visual content generation and editing, personalized virtual try-on, and automated quality assurance. You will develop the foundational capabilities that enable customers to express and discover styles through multimodal conversation and receive personalized, visual responses that bring their ideas to life. Your scientific approach will emphasize accurate, real-time visual understanding and generation, contextual understanding, and scalable personalization, enabling agentic AI to actively collaborate with customers to achieve their style goals. You will bring together computer vision, natural language processing, generative AI, and human-centered design to create agentic shopping experiences that are as intuitive as talking to a human specialist with a deep domain knowledge base. Success requires establishing robust metrics, collaborating with cross-functional partners, validating asset effectiveness across diverse customer touch points, and staying at the forefront of rapid advances in AI technology. The ideal candidate will have deep technical expertise in Computer Vision, Generative AI, or related fields with a strong ability to connect scientific work to customer and business outcomes. You will partner with scientists, engineers, and stakeholders across Amazon to deliver innovation and uphold a culture of scientific excellence and customer obsession. This role requires both rigorous research skills and practical engineering instincts, with a focus on delivering solutions that scale. This is a unique opportunity to shape the future of visual commerce through applied AI research, building the systems that will define how hundreds of millions of customers discover and evaluate products and styles through visual experiences. Key job responsibilities Innovation & Technical Execution • Develop core science primitives for vision and language understanding, visual content generation and editing, virtual try-on, and automated quality assurance via state-of-the-art computer vision, machine learning, and generative AI • Design and implement visual agentic systems, balancing visual quality, relevance, latency, and cost • Define metrics and success criteria for your scientific initiatives, ensuring rigorous validation across customer touch points • Own end-to-end delivery of research initiatives from problem formulation through experimentation to production deployment • Stay current with latest advances in AI/ML and identify opportunities to apply them to your problem space • Drive development and deployment of scalable agentic systems for visual content understanding and generation • Maintain high scientific and engineering standards in your work • Tackle complex technical problems while maintaining practical focus on customer value • Contribute to the team's culture of scientific excellence through presentations and publications at internal and external science forums Cross-functional Collaboration • Partner with product and engineering teams to deliver customer-facing features • Collaborate with scientists and engineers across multiple teams within Amazon to align on technical approaches • Communicate research findings and technical trade-offs clearly to both technical and non-technical stakeholders

Amazon is investing heavily in building a world class advertising business and we are responsible for defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities. The ATT team, based in Bangalore, is responsible for ensuring that ads are relevant and are of good quality, leading to higher conversion for the sellers and providing a great experience for the customers. We deal with one of the world’s largest product catalog, handle billions of requests a day with plans to grow it by an order of magnitude and use automated systems to validate tens of millions of offers submitted by thousands of merchants in multiple countries and languages. In this role, you will build and develop ML models to address content understanding and labeling problems in Ads. These models will rely on a variety of visual and textual features requiring expertise in both domains. These models need to scale to multiple languages and countries. You will collaborate with engineers and other scientists to build, train and deploy these models. As part of these activities, you will develop production level code that enables labeling of advertising assets and moderation of millions of ads submitted each day.

The Private Brands team is looking for a Sr. Applied Scientist to join the team in building science solutions at scale. Our team applies Optimization, Machine Learning, Statistics, Causal Inference, and Econometrics/Economics to derive actionable insights about the complex economy of Amazon’s retail business and develop Statistical Models and Algorithms to drive strategic business decisions and improve operations. We are an interdisciplinary team of Scientists, Engineers, and Economists. Key job responsibilities You will work with business leaders, scientists, and economists to translate business and functional requirements into concrete deliverables, including the design, development, testing, and deployment of highly scalable optimization solutions and ML models. This is a unique, high visibility opportunity for someone who wants to have business impact, dive deep into large-scale problems, enable measurable actions on the consumer economy, and work closely with scientists and economists. As a Sr Scientist, you bring business and industry context to science and technology decisions. You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems, acquiring expertise as needed. You decompose complex problems into straightforward solutions. We are particularly interested in candidates with experience in Operations Research and predictive models and working with distributed systems. Academic and/or practical background in Operations Research, Machine Learning and Reinforcement Learning are particularly relevant for this position. To know more about Amazon science, Please visit https://www.amazon.science

We are seeking an Applied Scientist to join Compass. In this role, you will develop the core Control Barrier Function (CBF) algorithms that form the mathematical foundation of the Compass safety system. You will ensure they don't just work in theory but perform reliably on real robots under real-world conditions. You will push the boundaries of concepts central to CBFs: computing robust invariant sets, designing hybrid system formulations that handle contact transitions and mode switches, and developing backup-set approaches that leverage learned policies and multiple controllers. A key challenge of this role is bridging the gap between the mathematics of set invariance and the realities of hardware, including sensor noise, model uncertainty, computational budgets, and discrete state transitions. You will ensure that these algorithms are not only provably correct but also implementable within a safety-critical architecture that must be certified by a third-party. You will contribute directly to the next generation of CBF theory and its practical deployment across Amazon's diverse robot fleet. Key job responsibilities • Develop and implement novel CBF algorithms that provide formal safety guarantees while minimizing conservatism to maximize the permissible operating envelope for each robot platform • Compute and refine invariant sets for complex, high-dimensional robotic systems, developing scalable methods that go beyond what existing analytical approaches can handle • Design formulations for hybrid dynamical systems, handling discrete mode transitions (e.g., contact/no-contact, stance/flight phases) with provable safety across switching boundaries • Address the theory-to-practice gap by developing methods that are robust to model uncertainty, sensor noise, actuation delays, and computational latency • Create reduced-order and full-order dynamics models with both white-box and black-box approach • Implement real-time optimization solvers that execute within the tight timing budgets of safety-critical control loops • Develop formal arguments and documentation sufficient to support third-party safety certification of algorithms • Validate algorithms through rigorous simulation and hardware experiments, characterizing failure modes and quantifying safety margins • Contribute to the theoretical foundations of CBFs through publications at top-tier controls and robotics venues • Collaborate with perception, planning, locomotion, and manipulation teams to accommodate the needs of upstream and downstream systems 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.

Our team in Amazon Robotics builds robotic systems that perform contact-rich manipulation tasks safely and reliably in complex, unstructured environments — at Amazon scale. Our scientists and engineers push the boundaries of robotic manipulation to handle enormous object diversity, bringing deep expertise across planning, control, perception, and machine learning. We learn from real-world data at a scale that few teams in robotics can access. We are seeking an Applied Scientist to join our Motion Behaviors team. You will design, implement, and deploy control strategies, manipulation behaviors, and affordance generation methods for contact-rich tasks on robots operating in Amazon fulfillment centers — spanning both engineered and learned approaches. You will validate your work through simulation and real-world testing, leveraging rich operational data to systematically improve system performance. Key job responsibilities • Design, implement, and deploy motion planning, control, and manipulation algorithms on production robotic systems. • Partner with experts across disciplines including perception, hardware and software to create intelligent, integrated systems and solutions. • Contribute to the development of learned manipulation behaviors and controllers, including sim-to-real deployment. • Write production-quality code and own scalable, real-time implementations. • Validate algorithms on hardware, iterating between simulation and real-world testing to ensure robust performance. • Analyze experimental results, identify failure modes, and drive systematic improvements to system performance. • Champion Amazon in academia through publications and scientific presentations. A day in the life Amazon offers a full range of benefits for you and eligible family members, including domestic partners. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!