Careers

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

Amazon Search is building a first-of-its-kind AI-powered visual search experience that lets customers describe products they're imagining, instantly see AI-generated images in response, and tap those images to search for matching products to shop. We are transforming the search engine into a shopping engine by leveraging advances in generative AI and multimodal understanding. We are seeking an Applied Scientist II to join the Visual Search Science team and push the boundaries of generative AI and multimodal retrieval at Amazon scale. You will work at the intersection of diffusion models, large language models (LLMs), and multimodal search to build systems that generate product visualizations in real time and connect them to Amazon's billions-scale catalog. The ideal candidate has deep expertise in one or more of the following areas: text-to-image generation, multimodal retrieval, LLM-based classification, AI safety and content moderation, or retrieval-conditioned generation. You will operate with startup-level autonomy backed by the resources of Amazon Search, serving hundreds of millions of customers worldwide. Key job responsibilities You will design, train, and optimize generative AI models for real-time product image generation, ensuring outputs meet strict latency requirements while maintaining high visual quality and query alignment. You will develop multimodal retrieval systems that connect AI-generated images to Amazon's billions-scale product catalog, optimizing for recall and ranking relevance across product categories. A core part of the role involves building LLM-based classifiers for visual intent detection, query understanding, and safety filtering within real-time latency budgets. You will advance AI safety science through defense-in-depth approaches including embedding-space classifiers, adversarial data engines, and post-generation content moderation. You will design and execute large-scale online experiments to measure impact on customer engagement, search success, and business metrics, defining evaluation frameworks that combine automated metrics with human judgment. You will collaborate with engineering, product, and design teams to architect GPU-intensive inference pipelines serving real-time traffic at scale, and contribute to Amazon's scientific community through publications and patents. About the team The Visual Search Science team is pioneering generative AI for shopping within Amazon Search. We sit at the intersection of computer vision, natural language processing, and information retrieval building systems that help customers visualize what they're looking for and seamlessly discover matching products. Our team operates with speed and autonomy while leveraging Amazon's massive scale, GPU infrastructure, and product catalog. We are a tight-knit group of scientists and engineers who value rigorous experimentation, creative problem-solving, and shipping innovations that customers love. We collaborate closely with partner teams across Search organization.

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.

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.

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.

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

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