Careers

We’re working to improve shopping on Amazon using the conversational capabilities of large language models, and are searching for pioneers who are passionate about technology, innovation, and customer experience, and are ready to make a lasting impact on the industry. In this role, you will be developing Multimodal and Agentic LLMs to unlock new shopping experiences. Experience in Vision-Language Multimodal Modeling and Reinforcement Learning is preferred. You'll be working with talented scientists, engineers, and technical program managers (TPM) to innovate on behalf of our customers. If you're fired up about being part of a dynamic, driven team, then this is your moment to join us on this exciting journey!

**This is an experimental role to support a business pilot and can potentially span up to 12 months** Embark on a transformative journey as our Sr. Domain Expert Lead, where intellectual rigor meets technological innovation. As a Sr. Domain Expert Lead, you will blend your advanced analytical skills and domain expertise to provide strategic oversight to our human-in-the-loop and model-in-the-loop data pipelines. You will also provide mentorship and guidance to junior team members. Your responsibilities will ensure data excellence through strategic oversight of high-quality data output, while delivering expert consultation throughout the pipeline and fostering iterative development. This position directly impacts the effectiveness and reliability of our AI solutions by maintaining the highest standards of data quality throughout the development process while building capability within the broader team. Key job responsibilities • Serve as a trusted domain advisor to cross-functional teams, providing strategic direction and specialized problem-solving support • Champion domain knowledge sharing across multiple channels and teams to maintain data quality excellence and standardization • Drive collaborative efforts with science teams to optimize output of complex data collections in your domain expertise, ensuring data excellence through iterative feedback loops • Foster team excellence through mentorship and motivation of peers and junior team members • Make informed decisions on behalf of our customers, ensuring that selected code meets industry standards, best practices, and specific client needs • Collaborate with AI teams to innovate model-in-the-loop and human-in-the-loop approaches, to ensure the collection of high-quality data, safeguarding data privacy and security for LLM training, and more. • Stay abreast of the latest developments in how LLMs and GenAI can be applied to your area of expertise to ensure our evaluations remain cutting-edge. • Develop and write demonstrations to illustrate "what good data looks like" in terms of meeting benchmarks for quality and efficiency • Provide detailed feedback and explanations for your evaluations, helping to refine and improve the LLM's understanding and output

Amazon Industrial Robotics is seeking exceptional talent to help develop the next generation of advanced robotics systems that will transform automation at Amazon's scale. We're building revolutionary robotic systems that combine cutting-edge AI, sophisticated control systems, and advanced mechanical design to create adaptable automation solutions capable of working safely alongside humans in dynamic environments. This is a unique opportunity to shape the future of robotics and automation at an unprecedented scale, working with world-class teams pushing the boundaries of what's possible in robotic dexterous manipulation, locomotion, and human-robot interaction. This role presents an opportunity to shape the future of robotics through innovative applications of deep learning and large language models. At Amazon Industrial Robotics we leverage advanced robotics, machine learning, and artificial intelligence to solve complex operational challenges at an unprecedented scale. Our fleet of robots operates across hundreds of facilities worldwide, working in sophisticated coordination to fulfill our mission of customer excellence. We are pioneering the development of systems that: • Enables unprecedented generalization across diverse tasks • Enables contact-rich manipulation in different environments • Seamlessly integrates mobility and manipulation • Leverage mechanical intelligence, multi-modal sensor feedback and advanced control techniques. The ideal candidate will contribute to research that bridges the gap between theoretical advancement and practical implementation in robotics. You will be part of a team that's revolutionizing how robots learn, adapt, and interact with their environment. Join us in building the next generation of intelligent robotics systems that will transform the future of automation and human-robot collaboration!

Amazon Industrial Robotics is seeking exceptional talent to help develop the next generation of advanced robotics systems that will transform automation at Amazon's scale. We're building revolutionary robotic systems that combine cutting-edge AI, sophisticated control systems, and advanced mechanical design to create adaptable automation solutions capable of working safely alongside humans in dynamic environments. This is a unique opportunity to shape the future of robotics and automation at an unprecedented scale, working with world-class teams pushing the boundaries of what's possible in robotic dexterous manipulation, locomotion, and human-robot interaction. This role presents an opportunity to shape the future of robotics through innovative applications of deep learning and large language models. At Amazon Industrial Robotics we leverage advanced robotics, machine learning, and artificial intelligence to solve complex operational challenges at an unprecedented scale. Our fleet of robots operates across hundreds of facilities worldwide, working in sophisticated coordination to fulfill our mission of customer excellence. - We are pioneering the development of robotics dexterous end-effectors that: - Enable unprecedented generalization across diverse tasks - Are compliant but at the same time impact resistant - Can enable power grasps with the same reliability as fine dexterity and nonprehensile manipulation - Can naturally cope with the uncertainty of the environment - Leverage mechanical intelligence, multi-modal sensor feedback and advanced control techniques. The ideal candidate will contribute to research that bridges the gap between theoretical advancement and practical implementation in robotics. You will be part of a team that's revolutionizing how robots learn, adapt, and interact with their environment. Join us in building the next generation of intelligent robotics systems that will transform the future of automation and human-robot collaboration. Key job responsibilities - Design and implement novel sensing and actuation technologies for dexterous manipulation - Develop parallel paths for rapid finger design and prototyping combining different actuation and sensing technologies as well as different finger morphologies - Develop new testing and validation strategies to support fast continuous integration and modularity - Build and test full hand prototypes to validate the performance of the solution - Create hybrid approaches combining different actuation technologies, under-actuation, active and passive compliance - Hand integration into rest of the embodiment - Partner with cross-functional teams to rapidly create new concepts and prototypes - Work with Amazon's robotics engineering and operations teams to grasp their requirements and develop tailored solutions - Document the designs, performance, and validation of the final system

Amazon Pay strives to be Earth’s most customer-centric payments service. Our mission is to serve customers and merchant partners with the most trusted, friction-less and rewarding payment solutions for their needs on and off Amazon. We are seeking an exceptional Data Scientist III to drive innovation in machine learning and artificial intelligence solutions while leading high-impact initiatives across the organization. Key job responsibilities Technical Excellence Lead end-to-end machine learning projects using PyTorch, AWS SageMaker, and other leading ML frameworks Design and implement complex statistical models and deep learning solutions Develop and optimize MLOps pipelines for model training, evaluation, and deployment Experience with modern LLM frameworks and Generative AI applications Expertise in Python, R, and related data science libraries MLOps & Development Build automated ML pipelines using AWS services (CodePipeline, Lambda, Step Functions) Implement CI/CD practices for ML model deployment and monitoring Create containerized solutions using Docker for scalable model deployment Experience with model optimization and hyperparameter tuning using tools like Optuna Integrate ML solutions with monitoring tools like MLflow Business Impact & Leadership Partner with stakeholders to translate business problems into technical solutions Design and develop business intelligence applications for real-time insights Lead technical initiatives and mentor junior data scientists Drive cross-functional collaboration to deliver innovative solutions Communicate complex technical concepts to non-technical audiences About the team The Amazon Pay Data Products team is a central unit that builds and maintains data products supporting Amazon Pay's growth across multiple markets. We operate at scale, processing 150M+ monthly transactions and managing 12 PB of data infrastructure. Our team consists of Business Intelligence Engineers, Data Engineers, and Product Managers who develop and maintain standardized reporting, data marts, and self-service analytics tools. Our expanded capabilities cover data science and Gen AI wherein we have built our first suite of multi-agent systems.

Are you passionate about applying machine learning and advanced statistical techniques to protect one of the world's largest online marketplaces? Do you want to be at the forefront of developing innovative solutions that safeguard Amazon's customers and legitimate sellers while ensuring a fair and trusted shopping experience? Do you thrive in a collaborative environment where diverse perspectives drive breakthrough solutions? If yes, we invite you to join the Amazon Risk Intelligence Science Team. We're seeking an exceptional scientist who can revolutionize how we protect our marketplace through intelligent automation. As a key member of our team, you'll develop and deploy state-of-the-art machine learning systems that analyze millions of seller interactions daily, ensuring the integrity and trustworthiness of Amazon's marketplace while scaling our operations to new heights. Your work will directly impact the safety and security of the shopping experience for hundreds of millions of customers worldwide, while supporting the growth of honest entrepreneurs and businesses. Key job responsibilities • Use machine learning and statistical techniques to create scalable abuse detection solutions that identify fraudulent seller behavior, account takeovers, and marketplace manipulation schemes • Innovate with the latest GenAI technology to build highly automated solutions for efficient seller verification, transaction monitoring, and risk assessment • Design, develop and deploy end-to-end machine learning solutions in the Amazon production environment to prevent and detect sophisticated abuse patterns across the marketplace • Learn, explore and experiment with the latest machine learning advancements to protect customer trust and maintain marketplace integrity while supporting legitimate selling partners • Collaborate with cross-functional teams to develop comprehensive risk models that can adapt to evolving abuse patterns and emerging threats About the team You'll be working closely with business partners and engineering teams to create end-to-end scalable machine learning solutions that address real-world problems. You will build scalable, efficient, and automated processes for large-scale data analyses, model development, model validation, and model implementation. You will also be providing clear and compelling reports for your solutions and contributing to the ongoing innovation and knowledge-sharing that are central to the team's success.

As an Applied Scientist on our Central Learning Solutions Team, you will play a critical role in driving the design, development, and delivery of learning programs and initiatives aimed at enhancing leadership and associate development within the organization. You will leverage your expertise in learning science, data analysis, and statistical model design to create impactful learning journey roadmap that align with organizational goals and priorities. Key job responsibilities Research and Analysis: - Conduct research on learning and development trends, theories, and best practices related to leadership and associate development - Analyze data to identify learning needs, performance gaps, and opportunities for improvement within the organization. - Use data-driven insights to inform the design and implementation of learning interventions. Program Design and Development: - Collaborate with cross-functional teams to develop comprehensive learning programs focused on leadership development and associate growth - Design learning experiences using evidence-based instructional strategies, adult learning principles, and innovative technologies. - Create engaging and interactive learning materials, including e-learning modules, instructor-led workshops, and multimedia resources. Evaluation and Continuous Improvement: - Develop evaluation frameworks to assess the effectiveness and impact of learning programs on leadership development and associate performance - Collect and analyze feedback from participants and stakeholders to identify strengths, areas for improvement, and future learning needs. - Iterate on learning interventions based on evaluation results and feedback to continuously improve program outcomes Thought Leadership and Collaboration: - Serve as a subject matter expert on learning science, instructional design, and leadership development within the organization - Collaborate with stakeholders across the company to align learning initiatives with strategic priorities and business objectives - Share knowledge and best practices with colleagues to foster a culture of continuous learning and development.

Join Amazon's Last Mile Technology Revolution! Are you ready to reshape the future of logistics? Join us in transforming how millions of packages reach their final destination through state-of-the-art technology and innovation! The Last Mile Technology organization is pioneering advanced solutions that are revolutionizing Amazon Logistics (AMZL). Our mission is to create intelligent, efficient, and scalable systems that will transform the delivery experience. We're building the future of last-mile logistics while maintaining Amazon's highest standards for safety and reliability. The Last Mile challenge is a fascinating blend of real-world complexity and technological innovation. We're tackling multidimensional problems that involve enabling AI agents to perceive and navigate complex delivery environments, understanding dynamic scenes through visual data, and adapting to everything from unexpected obstacles to varying weather and lighting conditions – all while ensuring every package arrives safely as per our promise. As an Applied Scientist on our Last Mile Technology team, you'll be at the forefront of developing computer vision and perception systems that enable us to understand and interact with the physical world. You'll design and implement deep learning models for visual perception, build algorithms that enable decision-making, and create robust systems that allow AI agents to operate safely across diverse geographical areas. Your research must excel in environments ranging from dense urban centers to suburban neighborhoods, each presenting unique visual and navigational challenges that require innovative solutions in perception and control. What Makes This Role Exciting: Real-World Impact: Your computer vision models and control algorithms will power AI agents that deliver millions of packages to customers, making their lives better every day Scale That Matters: Develop perception systems that operate across thousands of delivery agents in different cities, weather conditions, lighting scenarios, and dynamic environments Innovation at Scale: Publish novel research and create entirely new approaches to visual perception, scene understanding, and control systems End-to-End Science: Work on complete solutions from object detection and tracking to path planning and control, from sim-to-real transfer to real-world deployment and continuous learning from agent experiences

Are you interested in a unique opportunity to advance the accuracy and efficiency of Artificial General Intelligence (AGI) systems? If so, you're at the right place! We are the AGI Autonomy organization, and we are looking for a driven and talented Member of Technical Staff to join us to build state-of-the art agents. As an MTS on our team, you will design, build, and maintain a Spark-based infrastructure to process and manage large datasets critical for machine learning research. You’ll work closely with our researchers to develop data workflows and tools that streamline the preparation and analysis of massive multimodal datasets, ensuring efficiency and scalability. We operate at Amazon's large scale with the energy of a nimble start-up. If you have a learner's mindset, enjoy solving challenging problems and value an inclusive and collaborative team culture, you will thrive in this role, and we hope to hear from you. Key job responsibilities * Develop and maintain reliable infrastructure to enable large-scale data extraction and transformation. * Work closely with researchers to create tooling for emerging data-related needs. * Manage project prioritization, deliverables, timelines, and stakeholder communication. * Illuminate trade-offs, educate the team on best practices, and influence technical strategy. * Operate in a dynamic environment to deliver high quality software. About the team The Amazon AGI SF Lab is focused on developing new foundational capabilities for enabling useful AI agents that can take actions in the digital and physical worlds. In other words, we’re enabling practical AI that can actually do things for us and make our customers more productive, empowered, and fulfilled. The lab is designed to empower AI researchers and engineers to make major breakthroughs with speed and focus toward this goal. Our philosophy combines the agility of a startup with the resources of Amazon. By keeping the team lean, we’re able to maximize the amount of compute per person. Each team in the lab has the autonomy to move fast and the long-term commitment to pursue high-risk, high-payoff research.

We are looking for a passionate Applied Scientist to help pioneer the next generation of agentic AI applications for Amazon advertisers. In this role, you will design agentic architectures, develop tools and datasets, and contribute to building systems that can reason, plan, and act autonomously across complex advertiser workflows. You will work at the forefront of applied AI, developing methods for fine-tuning, reinforcement learning, and preference optimization, while helping create evaluation frameworks that ensure safety, reliability, and trust at scale. You will work backwards from the needs of advertisers—delivering customer-facing products that directly help them create, optimize, and grow their campaigns. Beyond building models, you will advance the agent ecosystem by experimenting with and applying core primitives such as tool orchestration, multi-step reasoning, and adaptive preference-driven behavior. This role requires working independently on ambiguous technical problems, collaborating closely with scientists, engineers, and product managers to bring innovative solutions into production. Key job responsibilities - Lead business, science and engineering strategy and roadmap for Sponsored Products Agentic Advertiser Guidance. - Design and build agents to guide advertisers in conversational and non-conversational experience. - Design and implement advanced model and agent optimization techniques, including supervised fine-tuning, instruction tuning and preference optimization (e.g., DPO/IPO). - Curate datasets and tools for MCP. - Build evaluation pipelines for agent workflows, including automated benchmarks, multi-step reasoning tests, and safety guardrails. - Develop agentic architectures (e.g., CoT, ToT, ReAct) that integrate planning, tool use, and long-horizon reasoning. - Prototype and iterate on multi-agent orchestration frameworks and workflows. - Collaborate with peers across engineering and product to bring scientific innovations into production. - Stay current with the latest research in LLMs, RL, and agent-based AI, and translate findings into practical applications. About the team The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through the latest generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. The Advertiser Guidance team within Sponsored Products and Brands is focused on guiding and supporting 1.6MM advertisers to meet their advertising needs of creating and managing ad campaigns. At this scale, the complexity of diverse advertiser goals, campaign types, and market dynamics creates both a massive technical challenge and a transformative opportunity: even small improvements in guidance systems can have outsized impact on advertiser success and Amazon’s retail ecosystem. Our vision is to build a highly personalized, context-aware agentic advertiser guidance system that leverages LLMs together with tools such as auction simulations, ML models, and optimization algorithms. This agentic framework, will operate across both chat and non-chat experiences in the ad console, scaling to natural language queries as well as proactively delivering guidance based on deep understanding of the advertiser. To execute this vision, we collaborate closely with stakeholders across Ad Console, Sales, and Marketing to identify opportunities—from high-level product guidance down to granular keyword recommendations—and deliver them through a tailored, personalized experience. Our work is grounded in state-of-the-art agent architectures, tool integration, reasoning frameworks, and model customization approaches (including tuning, MCP, and preference optimization), ensuring our systems are both scalable and adaptive.