Careers

Amazon's Community Intelligence Science & Engineering (CISE) team operates at the intersection of computational social science, artificial intelligence, and operational planning. We build and validate models that quantify how Amazon's operational presence impacts local communities, and embed those signals into core planning models that drive Last Mile, Middle Mile, and site-level decisions across our network. You'll work at the forefront of applied AI and causal inference, building systems that influence decisions affecting thousands of communities daily. This role offers a unique opportunity to shape how the world's most customer-centric company measures, forecasts, and reduces operational risk to the communities we serve. A successful Senior Research Scientist on our team demonstrates exceptional scientific rigor combined with pragmatic execution. You will design the causal frameworks and predictive models that systematically embed these community signals into core operational planning processes where they do not yet exist. This means balancing breakthrough research with production deployment, collaborating across multiple science organizations, and translating complex analytical findings into actionable insights that influence senior leadership strategy. As a Senior Research Scientist, you will partner with product teams, operational scientists, and technical leaders across Last Mile Planning Science, Middle Mile Relay, Safety, and Worldwide Operations Security to identify opportunities where community intelligence creates multiplicative business impact. Key job responsibilities - Collaborate with operational science teams to integrate community risk signals into existing operational models and decision-making systems, with a focus on quantifying performance lift and defining integration architecture - Design and execute experiments to measure how community-impacting operational policies affect business outcomes - Build automated causal discovery systems leveraging knowledge graphs, LLMs, and document understanding to uncover relationships between operational policies and community outcomes - Design and deploy production ML forecasting systems with extended prediction horizons using multi-modal data sources, including survey-based indices, geospatial risk features, and operational metrics - Mentor junior scientists and contribute to building a research culture that balances high-risk, high-reward innovation with reliable product delivery About the team Amazon Community Operations (CommOps) works to anticipate our communities’ needs and build positive net impact anywhere we operate. From Operational Excellence to Community Outreach, Community Operations is defining what it means to be a positive presence in the community. This is a fast-paced, start-up environment where creative problem solving, operational excellence, and building relationships are the core of our day-to-day work.

The Amazon Q Developer Science team is looking for an Applied Scientist who is passionate about building services and tools for developers that leverage artificial intelligence (AI) agents and machine learning (ML). You will be part of a team building AI-based services for Amazon Q Developer with the focus on redefining the way developer work. The team works in close collaboration with other AWS AI services such as AWS Bedrock, the AWS IDE Toolkit, and Amazon Sagemaker. If you are excited about working in cloud computing and building new AWS services, then we'd love to talk to you. Key job responsibilities As a senior Applied Scientist, you are recognized for your expertise, advise team members on a range of machine learning topics, and work closely with software engineers to drive the delivery of end-to-end modeling solutions. Your work focuses on ambiguous problem areas where the business problem or opportunity may not yet be defined. The problems that you take on require scientific breakthroughs. You take a long-term view of the business objectives, product roadmaps, technologies, and how they should evolve. You drive mindful discussions with customers, engineers, and scientist peers. You bring perspective and provide context for current technology choices, and make recommendations on the right modeling and component design approach to achieve the desired customer experience and business outcome. About the team Why AWS Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Utility Computing (UC) AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (IoT), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. 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 we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Mentorship and 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, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred 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.

The Artificial General Intelligence (AGI) team is seeking a dedicated, skilled, and innovative Applied Scientist with a robust background in machine learning, statistics, quality assurance, auditing methodologies, and automated evaluation systems to ensure the highest standards of data quality, to build industry-leading technology with Large Language Models (LLMs) and multimodal systems. Key job responsibilities As part of the AGI team, an Applied Scientist will collaborate closely with core scientist team developing Amazon Nova models. They will lead the development of comprehensive quality strategies and auditing frameworks that safeguard the integrity of data collection workflows. This includes designing auditing strategies with detailed SOPs, quality metrics, and sampling methodologies that help Nova improve performances on benchmarks. The Applied Scientist will perform expert-level manual audits, conduct meta-audits to evaluate auditor performance, and provide targeted coaching to uplift overall quality capabilities. A critical aspect of this role involves developing and maintaining LLM-as-a-Judge systems, including designing judge architectures, creating evaluation rubrics, and building machine learning models for automated quality assessment. The Applied Scientist will also set up the configuration of data collection workflows and communicate quality feedback to stakeholders. An Applied Scientist will also have a direct impact on enhancing customer experiences through high-quality training and evaluation data that powers state-of-the-art LLM products and services. A day in the life An Applied Scientist with the AGI team will support quality solution design, conduct root cause analysis on data quality issues, research new auditing methodologies, and find innovative ways of optimizing data quality while setting examples for the team on quality assurance best practices and standards. Besides theoretical analysis and quality framework development, an Applied Scientist will also work closely with talented engineers, domain experts, and vendor teams to put quality strategies and automated judging systems into practice.

We are working on improving shopping on Amazon using the conversational capabilities of large language models and through customer behavioral data to make them more personalized for each customer. We 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 managing a team working on Large Language Model (LLM) and/or Vision-Language Model (VLM) post-training and alignment for new shopping experiences. 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 Expert Consultant, where intellectual rigor meets technological innovation. As an Expert Consultant, 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

The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry leading 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. We are the Sponsored Products - Marketplace Intelligence (MI) team. We are looking for an Applied Scientist to help build production ML and bandit solutions to customize the search experience. We determine which ads to show in Amazon search, where to place them, how many ads to place, and to which customers. This helps shoppers discover new products while helping advertisers put their products in front of the right customers, aligning shoppers’, advertisers’, and Amazon’s interests. To do this, we apply a broad range of machine learning, causal inference, and optimization techniques to continuously explore, learn, and optimize the allocation and ranking of ads on the search page. We are an interdisciplinary team with a focus on customer obsession and inventing and simplifying. Our primary focus is on improving the SP experience in search by gaining a deep understanding of shopper pain points and developing new innovative solutions to address them. You will be on the Search Ad Ranking and Interleaving team org - specifically the team that focusses on whole page optimization. Our mission is to personalize and contextualize SP ad allocation on the entire search page. We do this by modeling shopper responses to the number, placement, and quality of ads. We are a data- and hypothesis-driven organization that uses online experimentation, simulation, causal modeling, and online feedback to place ads where they’re useful to shoppers and provide improved discoverability and sales for advertisers. This is a unique opportunity for someone who wants to have broad business impact, a direct impact on customers and the search experience, and get broad exposure to a wide range of scientific techniques (machine learning, bandit learning, optimization, LLMs). We are looking for an Applied Scientist to join Interleaving team in Marketplace Intelligence with a broad mandate to experiment and innovate to grow Sponsored Products. We’d like someone with practical experience with LLMs / GenAI for production to improve how we rank and allocate ads on the page today. If you thrive in a product-focussed and data-driven environment, then this role is for you. As a Applied Scientist on this team, you will help to identify unique opportunities to create customized and delightful shopping experience for our growing marketplaces worldwide. Your job will be to identify big opportunities for the team that can help to grow Sponsored Products business working with retail partner teams, product managers, software engineers and TPMs. You will have opportunity to design, run and analyze / experiments to improve the experience of millions of Amazon shoppers while driving quantifiable revenue impact. More importantly, you will have the opportunity to broaden your technical skills in an environment that thrives on creativity, experimentation, and product innovation. Key job responsibilities * Tackle and solve challenging science and business problems that balance the interests of advertisers, shoppers, and Amazon. * Develop real-time machine learning algorithms to allocate billions of ads per day in advertising auctions. * Develop efficient algorithms for multi-objective optimization and AI control methods to find operating points for the ad marketplace then evolve them * Be an expert at designing and implementing solutions that use a range of data science methodologies to automate data analysis or to solve complex business problems. * Perform hands-on analysis and modeling of enormous data sets to develop insights that improve shopper experience, without compromising Ad revenue in addition to designing metrics for complex systems. * Drive end-to-end machine learning projects that have a high degree of ambiguity, scale, complexity. * Run A/B experiments, gather data, and perform statistical analysis.

Are you passionate about revolutionizing the Architecture, Engineering, Construction, and Ownership (AECO) industry through next-generation artificial intelligence? AWS Data Center Design Engineering is seeking an exceptional Applied Scientist with Building Information Modeling (BIM) domain expertise to transform how we design and deliver Amazon's global data center infrastructure. In this role, you will build state-of-the-art machine learning systems that accelerate data center design workflows by automating building design tasks in BIM environments and ensuring compliance with building codes and design standards. You will work across both structured data (BIM models from Autodesk Revit, 3D geometries, spatial relationships) and unstructured data (construction drawings, specifications, submittals) to develop production-grade ML solutions. This position offers a unique science breadth, spanning graph neural networks, natural language processing, reinforcement learning, and computer vision, with the opportunity to research and apply novel techniques against real-world engineering challenges at unprecedented scale. You will collaborate closely with architects, structural engineers, MEP engineers, construction managers, UX designers, product managers, and software development teams to translate research innovations into deployed systems that deliver measurable customer impact. The ideal candidate combines strong theoretical foundations in machine learning with practical experience applying ML to domain-specific problems. You understand that AECO professionals maintain exceptionally high trust bars and require AI systems that augment rather than replace professional judgment. You thrive on solving hard problems at the intersection of ML research and domain expertise. Key job responsibilities - Drive end-to-end GenAI projects with high complexity and ambiguity from conception to production - Build, adapt, evaluate, and deploy ML models for BIM and AECO applications, collaborating with software engineers for productionization - Research innovative machine learning approaches and identify new opportunities for GenAI applications in the building engineering and design domain - Design and implement model architectures, train and fine-tune foundation models using domain-specific datasets, and optimize performance through iterative experimentation - Process and prepare training data, including data governance, provenance tracking, quality checks, and creating reusable data pipelines - Define research roadmaps aligned with business priorities, balancing foundational research with incremental product improvements for AECO applications - Represent the team in the broader science community, publishing findings, delivering tech talks, and staying at the forefront of GenAI and BIM research - Collaborate with a cross-functional team of ML scientists, building engineers, software engineers, UX designers, and product managers, and present results to senior leadership A day in the life About AIS AWS Infrastructure Services (AIS) owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we’re looking for talented people who want to help. You’ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion. About the team About AWS Diverse Experiences AWS 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 AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon conferences, inspire us to never stop embracing our uniqueness. Mentorship & 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, mentorship 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 we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. This job opportunity is available both for the full time and part time employment.

The People eXperience and Technology Central Science (PXTCS) team uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, well-being, and the value of work to Amazonians. The Benefits Science team is looking for an economist to transform complex business challenges into actionable scientific insights. In this role, you will partner directly with business leaders to design and evaluate pilots, build models using large-scale data, and scale successful prototypes into company-wide policies and programs. We're looking for someone who can combine rigorous scientific thinking with practical business acumen and is passionate about using economics to improve employee experiences at scale. The ideal candidate will thrive in interdisciplinary environments, working alongside engineers, data scientists, and business leaders from diverse backgrounds. Key job responsibilities - Design and conduct rigorous evaluations of benefits programs - Support the development and application of structural models - Develop experiments to evaluate the impact of benefits initiatives - Communicate complex findings to business stakeholders in clear, actionable terms - Work with engineering teams to develop scalable tools that automate and streamline evaluation processes A day in the life Work with teammates to apply economic methods to business problems. This might include identifying the appropriate research questions, writing code to implement a DID analysis or estimate a structural model, or writing and presenting a document with findings to business leaders. Our economists also collaborate with partner teams throughout the process, from understanding their challenges, to developing a research agenda that will address those challenges, to help them implement solutions.

The AGI Information organization is at the forefront of artificial intelligence and machine learning innovation, developing AI systems used across AWS, Alexa, and other Amazon businesses that transform how customers interact with information, in particular integrating a broad range of structured and unstructured information into AI systems (e.g. with RAG techniques). Our team combines world-class research with production-scale engineering to deliver impactful AI-driven products and services. We're looking for an experienced leader who can drive scientific excellence while building and mentoring high-performing teams of applied scientists and machine learning engineers. If you are deeply familiar with LLMs, natural language processing, and machine learning and have experience managing high-performing research teams, this may be the right opportunity for you. Our fast-paced environment requires a high degree of independence in making decisions and driving ambitious research agendas all the way to production. You will work with other science and engineering teams as well as business stakeholders to maximize velocity and impact of your team's contributions. It's an exciting time to be a leader in AI research. In Amazon's AGI Information team, you can make your mark by improving information-driven experience of Amazon customers worldwide! Key job responsibilities * Lead and manage teams of applied scientists and machine learning engineers, providing mentorship, career development, and performance management * Define and execute the technical roadmap for applied science initiatives, balancing innovation with business impact * Work with new technologies and methodologies that improve model performance, usability, and scalability of ML systems * Translate complex business requirements into technical deliverables and deliver operationally stable solutions that provide exceptional customer experiences * Participate in the full development cycle, end-to-end, from research and design to implementation, testing, documentation, delivery, and maintenance * Evaluate and make strategic decisions around the use of new or existing ML frameworks, tools, and technologies * Collaborate with Senior Engineers, Principal Engineers, and Principal Scientists across the organization to define architecture and research plans for the next three years * Drive scientific rigor through experimentation, A/B testing, and data-driven decision making Partner with cross-functional teams including product management, engineering, and business stakeholders to align science initiatives with business objectives * Publish research findings and represent Amazon at top-tier conferences and in the scientific community * Establish best practices for ML development, including model evaluation, monitoring, and continuous improvement

Amazon Rufus Experience Science is seeking a highly motivated Scientist who is passionate about building next-generation shopping experiences. In this role, you will help create conversational shopping journeys where customers can express any shopping need—discovering products, comparing options, finding inspiration, or resolving post-purchase issues. You will collaborate closely with a multidisciplinary team of scientists, engineers, product managers, and designers to deliver these experiences across multiple Rufus customer-facing features.
You will thrive in this role if you enjoy bringing latest research into everyday life—both for customers and for yourself. There’s nothing quite like realizing that a model you deployed yesterday is already improving your own shopping experience today. You will work side by side with scientists and engineers in a fast-paced environment, driving rapid model development and experimentation. You’ll also have access to Amazon’s rich datasets, AWS’s massive computational resources, and a network of world-class science and engineering leaders across the company. Key job responsibilities Translate the science roadmap into technical milestones, ensuring research efforts align with long-term business goals.

 Develop end-to-end data-driven solutions for the real-world, large scale problems.

 Deliver and maintain software and models in the production environment.
 
Collaborate cross-functionally between product, design, and engineering.