Careers

Amazon's Search Science and AI team creates ML algorithms that connect customers around the world with products that delight them. We harness cutting-edge ML at Amazon's scale to make the customer experience easier and smoother. Our impact is large. For example, if your innovations save even 1 minute per customer per year, then for every 100 million customers, you save approximately 190 years of human effort. Key job responsibilities You will build search ranking systems that work for thousands of product types, billions of queries, and hundreds of millions of customers spread around the world. As an Applied Scientist you will find the next set of big improvements to ranking, leverage large datasets to understand the complexities of customer behavior, and get your hands dirty by building ML models that work at Amazon scale. In addition to typical topics in ranking, we are particularly interested in exploration techniques and reinforcement learning. A day in the life Our primary focus is improving search ranking systems. On a day-to-day this means building ML models, analyzing data from your recent A/B tests, and guiding teams on best practices. You will also find yourself in meetings with business and tech leaders at Amazon communicating your next big initiative. About the team We are a team consisting of ML scientists and software engineers. Our interests and activities span machine learning for better ranking, statistics for better decision making, and infrastructure to make it all happen at scale and efficiently.

Amazon’s maps play a crucial role in our vehicle navigation, routing, and planning problems to ensure fast and safe deliveries to our customers. As part of the Last Mile Geospatial Science organization, you’ll partner closely with other scientists and engineers in a collegial environment with a clear path to business impact. We have an exciting problem area to augment the maps and routing inputs from satellite/aerial imagery and street videos by leveraging the latest computer vision and deep learning techniques. Key job responsibilities Successful candidates should have a deep knowledge (both theoretical and practical) of various machine learning algorithms for large scale computer vision problems, the ability to map models into production-worthy code, the communication skills necessary to explain complex technical approaches to a variety of stakeholders and customers, and the excitement to take iterative approaches to tackle big, long term problems. The applied scientist should be proficient with image and video analysis using machine learning, including designing architecture from scratch, modify existing loss functions, full model training, fine-tuning, and evaluating the latest deep learning models. The Applied Scientist optimizes different models for specific platforms, including edge devices with restricted resources. Multi-modal models, e.g., Large Vision Language Models (LVLM), zero-shot, few-shot, and semi-supervised learning paradigms are used extensively. A day in the life 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! 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

We are open to candidates located in: Seattle and Bellevue, Washington. As a Senior Data Scientist, you will be on the ground floor with your team, shaping the way performance is measured, defining what questions should be asked, and scaling analytics methods and tools to support our growing business. You will work closely with Data Engineers, Product Managers, Business Intelligence Engineers, and Software Engineers to develop statistical models, design and run experiments, and find new ways to to optimize the customer experience. A successful candidate is highly analytical, able to work effectively in a matrix organization, and adept at synthesizing a variety of technologies and capabilities into products that enhances the PXF experience across multiple products. You must engage with customers to deeply understand their current and emerging needs. PXF applications are rapidly evolving and our user base is rapidly expanding, as a DS on the team you will own diving into the different users personas and inventing on behalf of the app users to meet their needs. We are looking for someone who's customer obsessed and technology savvy - with a passion for app development work. The ideal candidate will have a well-rounded technical background as well as a history of leading complex, ambiguous projects end-to-end. Key job responsibilities - Partner with business stakeholders in formulating the business problem and providing recommendations on the approach - Understanding customer behavior to personalize customer experience, build recommendation engines to provide relevant results to customers, customer lifecycle analysis and usage behavior - Conduct large scale A/B testing and offline/online experiments to evaluate performance of various programs and drive product improvements across partner teams - Process large scale datasets using distributed computing platform to build models, mining insights from data and prototyping models that optimize towards various business goals and metrics - Interact with cross-functional teams and make business recommendations i.e cost-benefit, forecasting, experiment analysis and present findings to leadership team - Driving product roadmap and prioritizations of science projects with the PMs to improve customer experience About the team PXF builds the employee experiences that connect Amazonians, support them through their employment journey, and make Amazon Earth's Best Employer. Our products include A to Z mobile application directly impacts the lives of associates by helping them identify the best shifts for their schedule, opportunities to pick up additional work, and choose when they get paid. We enable Amazon employees to easily find and access high-quality and authoritative content throughout their employment lifecycle through content management and Search capabilities. We also provide employees with a dynamic and ever-evolving learning experience to protect, prepare, and advance their careers.

Do you want to be part of a team that's revolutionizing Amazon's fulfillment and packaging technology? Can you commit to optimizing systems that process tens-of-millions of customer packages daily with the lowest cost to serve and a defect-free customer experience? Do you have a passion for solving complex science challenges and building a sustainable e-commerce experience? Your Deep Learning skills can help make that a reality on the Mechatronics and Sustainable Packaging team. We are looking for a talented Senior Applied Scientist to join our team. You will join a team of Scientists and Machine Learning Engineers (MLEs) to directly improve the packaging experience of Amazon customers in the fulfillment technology space. The team consists of experts in the field of Statistics, Operational Research, Machine Learning (ML), Computer Vision and Generative AI who work together to break new ground in the world of automated packaging solutions. You'll work in a collaborative environment where you will deploy and scale ML solutions to peta-bytes of data, work on problems that haven’t been solved before, and understand whether they succeed via statistically relevant experiments across millions of customers. You'll see the work you do directly improve the packaging experience of Amazon customers in the fulfillment technology space. If you are interested in robotics, computer vision, machine learning, big data, and building scalable solutions, this role is for you. The successful candidate will have a PhD in Computer Science, Statistics, or Engineering with a strong focus on data analysis, machine learning, generative AI or a related field, and 5+ years of practical experience solving complex problems in computer vision, anomaly detection, robotics. or multi-modal classification systems. Manufacturing, packaging and/or logistic experience is a plus, but not a requirement. Key job responsibilities - Advance exploratory research projects in machine learning, statistics and related fields to create defect-free packaging customer experiences - Analyze large amounts of Amazon shipments to discover patterns, find opportunities, and develop highly innovative, scalable algorithms to seize these opportunities - Validate new or improved models via statistically relevant experiments across millions of customers - Work closely with software engineering teams to build scalable prototypes for testing, and integrate successful models and algorithms in production systems at very large scale

The Community Feedback organization powers customer-generated features and insights that help customers use the wisdom of the community to make unregretted shopping decisions. Today our features include Customer Reviews, Content Moderation, and Customer Q&A (Ask), however our mission and charter are broader than these features. We are focused on building a rewarding and engaging experience for contributors to share their feedback, and providing shoppers with trusted insights based on this feedback to inform their shopping decision The Community Data & Science team is looking for a passionate, talented, and inventive Senior Applied Scientist with a background in AI, Gen AI, Machine Learning, and NLP to help build LLM solutions for Community Feedback. You'll be working with talented scientists and engineers to innovate on behalf of our customers. If you're fired up about being part of a dynamic, driven team and are ready to make a lasting impact on the future of AI-powered shopping, we invite you to join us on this exciting journey to reshape shopping. Please visit https://www.amazon.science for more information. Key job responsibilities - As a Senior Applied Scientist, you will work on state-of-the-art technologies that will result in published papers. - However, you will not only theorize about the algorithms but also have the opportunity to implement them and see how they perform in the field. - Our team works on a variety of projects, including state-of-the-art generative AI, LLM fine-tuning, alignment, prompt engineering, and benchmarking solutions. - You will be also mentoring junior scientists on the team. About the team The Community Data & Science team focusses on analyzing, understanding, structuring and presenting customer-generated content (in the form of ratings, text, images and videos) to help customers use the wisdom of the community to make unregretted purchase decisions. We build and own ML models that help with i) shaping the community content corpus both in terms of quantity and quality, ii) extracting insights from the content and iii) presenting the content and insights to shoppers to eventually influence purchase decisions. Today, our ML models support experiences like content solicitation, submission, moderation, ranking, and summarization.

AMZL Global Fleet and Products (GFP) organization is responsible for fleet programs and capacity for Last Mile deliveries. The Fleet Planning team is looking for a Data Scientist to drive the most efficient use of fleet. Last Mile fleet planning is a complex resource allocation problem. The goal of fleet allocation planning is to optimize the size and mix of fleet allocated to DSPs through various programs to improve branded fleet utilization. Changes in routes, last mile network, exiting DSPs and new DSP onboarding create continuous need for re-allocation of fleet to maintain an efficient network capacity. This requires allocation to adhere to various operational limits (repair network, EV range, Station Charging capability) and also match route’s cube need to vehicles capacity. As a Data Scientist on the Fleet Planning team (GFP), you will be responsible for building new science models (linear programs, statistical and ML models) and enhancing existing models for changing business needs. You would work with program managers in planning, procurement, redeployment, deployment, remarketing, variable fleet and infrastructure programs to build models that would support the requirements of all programs in a coherent plan. Key job responsibilities • Build models and automation for planners for generating vehicle allocation plans • Partner with program teams to test and measure success of implemented model • Lead reviews with senior leadership, deep dive model outputs and explain implications of model recommendations.

About Amazon Health Amazon Health’s mission is to make it dramatically easier for customers to access the healthcare products and services they need to get and stay healthy. Towards this mission, we (Health Storefront and Shared Tech) are building the technology, products and services, that help customers find, buy, and engage with the healthcare solutions they need. Job summary We are seeking an exceptional Senior Applied Scientist to join a team of experts in the field of machine learning, and work together to break new ground in the world of healthcare to make personalized and empathetic care accessible, convenient, and cost-effective. We leverage and train state-of-the-art large-language-models (LLMs) and develop entirely new experiences to help customers find the right products and services to address their health needs. We work on machine learning problems for intent detection, dialogue systems, and information retrieval. You will work in a highly collaborative environment where you can pursue both near-term productization opportunities to make immediate, meaningful customer impacts while pursuing ambitious, long-term research. You will work on hard science problems that have not been solved before, conduct rapid prototyping to validate your hypothesis, and deploy your algorithmic ideas at scale. You will get the opportunity to pursue work that makes people's lives better and pushes the envelop of science. #everydaybetter Key job responsibilities - Translate product and CX requirements into science metrics and rigorous testing methodologies. - Invent and develop scalable methodologies to evaluate LLM outputs against metrics and guardrails. - Design and implement the best-in-class semantic retrieval system by creating high-quality knowledge base and optimizing embedding models and similarity measures. - Conduct tuning, training, and optimization of LLMs to achieve a compelling CX while reducing operational cost to be scalable. A day in the life In a fast-paced innovation environment, you work closely with product, UX, and business teams to understand customer's challenges. You translate product and business requirements into science problems. You dive deep into challenging science problems, enabling entirely new ML and LLM-driven customer experiences. You identify hypothesis and conduct rapid prototyping to learn quickly. You develop and deploy models at scale to pursue productizations. You mentor junior science team members and help influence our org in scientific best practices. About the team We are the Health AI team at HST (Health Store and Technology). The team consists of exceptional ML Scientists with diverse background in healthcare, robotics, customer analytics, and communication. We are committed to building and deploying the most advanced scientific capabilities and solutions for the products and services at Amazon Health.

Join us at the cutting edge of Amazon's sustainability initiatives to work on environmental and social advancements and support Amazon's long term worldwide sustainability strategy. At Amazon, we're working to be the most customer-centric company on earth. To get there, we need exceptionally talented, bright, and driven people. The Worldwide Sustainability (WWS) organization capitalizes on Amazon’s scale, speed, and ability to build, invent and simplify, a more resilient and sustainable company. We manage our social and environmental impacts globally, and drive solutions that enable our customers, businesses, and the world to become more sustainable. Sustainability Science and Innovation (SSI) is a multi-disciplinary team within the WW Sustainability organization that combines science, analytics, economics, statistics, machine learning, product development, and engineering expertise. We use this expertise and skills to identify, develop and evaluate the science and innovations necessary for Amazon, customers and partners to meet their long-term sustainability goals and commitments. The Sustainability Science and Innovation team is looking for an Applied Scientist to collaborate closely with Data Engineers, and ML and Environmental Scientists to build the data foundation of the future. You will help the team to define strategy and implement tooling to identify, ingest, harmonize, store, and develop models to utilize strategic data from both internal and external sources. These datasets must cover a wide range of topics such as geographic regions and data formats to unlock foundational AI research in emerging areas and applications. These solutions will support Amazon-wide sustainability initiatives like carbon footprinting, climate risk monitoring, and social responsibility through the supply chain. If you see yourself as a hands-on leader and innovator at the intersection of AI, data, and sustainability, we'd like to connect with you. You don't necessarily have to be an expert in sustainability and climate domains. Key job responsibilities - Design, implement, and maintain scalable machine learning infrastructure and pipelines for model development, training, and deployment across sustainability domains. - Develop and optimize state-of-the-art ML models and algorithms for processing diverse data types (images, text, structured data) from various sources, ensuring high performance and reliability. - Lead the implementation of Gen AI and foundational model development, fine-tuning, and benchmarking for sustainability-related tasks. - Establish and enforce MLOps best practices, including comprehensive monitoring, alarming, and model performance evaluation systems for all deployed ML models. - Collaborate with Data Scientists and Software Engineers to create ML experimentation strategies and integrate ML solutions into production environments efficiently. - Research and implement cutting-edge machine learning techniques to improve model accuracy, efficiency, and generalization across various sustainability applications. - Partner with cross-functional teams to identify and solve business problems using ML, while mentoring junior ML engineers and contributing to the development of ML engineering best practices within the organization. About the team Diverse Experiences: World Wide Sustainability (WWS) 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. Inclusive Team Culture: 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. 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 flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.

Amazon's Next Generation Developer Experience (NGDE) Organization is looking for world class scientists and engineers to join its team to work on AI4Code, LLM, and natural language processing. This group is entrusted with developing core algorithms/capabilities for Amazon Q Developer. At NGDE's science team you will invent, implement, and deploy state of the art AI algorithms and systems for developers. You will build prototypes and explore conceptually new large scale AI solutions. You will interact closely with our customers and with the academic community. You will be at the heart of a growing and exciting focus area for AWS and work with other acclaimed engineers and world famous scientists. About the team 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. 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 (gender diversity) 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. Hybrid Work We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices.

Are you passionate about using science to build disruptive solutions that challenge the status-quo? Do you want to fundamentally redefine talent management and development for one of the largest and most complex workforce in the world? If you are, we want to talk to you. Key job responsibilities We are looking for a Data Scientist generalist who can work with senior leadership and also partner with technical experts to deliver deliver best-in-class data science solutions for Amazon Talent. The Data Scientist will be comfortable leading statistical and ML projects from conception to production, including understanding business needs, transforming and exploring data, building and validating ML models, and deploying completed models on the AWS cloud. Finally, this person will be an expert at synthesizing and communicating insights and recommendations to audiences of varying levels of technical sophistication. A day in the life In this role you will closely partner with Amazon WW Stores, Finance, and HR leadership teams, and with various engineering, data, and science teams across the company. Your goal will be to discover best in class approaches to help better understand and forecast talent movement and enable your customers to derive actionable insights to inform talent strategies. You will develop scientific solutions grounded in rigorous experimentation and measurement to support the growth and mobilization of our workforce, and strategic organizational planning to ensure our talent is optimally positioned to capitalize on emerging business opportunities. About the team The Measurement & Insights team serves as the analytical backbone of Amazon Stores Talent Management, ensuring that Amazon Stores remains at the cutting edge of data-driven talent optimization in the rapidly evolving retail and e-commerce landscape. We focus on providing scientific insights to solve durable customer problems relating to talent optimization, organizational structure, and operating mechanisms. Our interdisciplinary science team with expertise in psychometric measurement, experimental and quasi-experimental research design, statistics, and machine learning, guide the metric design and scientific approaches, uncover blind spots, and provide proactive insights to address potential challenges and opportunities.