Careers

The Amazon Search Mission Understanding (SMU) team is at the forefront of revolutionizing the online shopping experience through the Amazon search page. Our ambition extends beyond facilitating a seamless shopping journey; we are committed to creating the next generation of intelligent shopping assistants. Leveraging cutting-edge Large Language Models (LLMs), we aim to redefine navigation and decision-making in e-commerce by deeply understanding our users' shopping missions, preferences, and goals. By developing responsive and scalable solutions, we not only accomplish the shopping mission but also foster unparalleled trust among our customers. Through our advanced technology, we generate valuable insights, providing a guided navigation system into various search missions, ensuring a comprehensive and holistic shopping experience. Our dedication to continuous improvement through constant measurement and enhancement of the shopper experience is crucial, as we strategically navigate the balance between immediate results and long-term business growth. We are seeking an Applied Scientist who is not just adept in the theoretical aspects of Machine Learning (ML), Artificial Intelligence (AI), and Large Language Models (LLMs) but also possesses a pragmatic, hands-on approach to navigating the complexities of innovation. The ideal candidate will have a profound expertise in developing, deploying, and contributing to the next-generation shopping search engine, including but not limited to Retrieval-Augmented Generation (RAG) models, specifically tailored towards enhancing the Rufus application—an integral part of our mission to revolutionize shopping assistance. You will take the lead in conceptualizing, building, and launching groundbreaking models that significantly improve our understanding of and capabilities in enhancing the search experience. A successful applicant will display a comprehensive skill set across machine learning model development, implementation, and optimization. This includes a strong foundation in data management, software engineering best practices, and a keen awareness of the latest developments in distributed systems technology. We are looking for individuals who are determined, analytically rigorous, passionate about applied sciences, creative, and possess strong logical reasoning abilities. Join the Search Mission Understanding team, a group of pioneering ML scientists and engineers dedicated to building core ML models and developing the infrastructure for model innovation. As part of Amazon Search, you will experience the dynamic, innovative culture of a startup, backed by the extensive resources of Amazon.com (AMZN), a global leader in internet services. Our collaborative, customer-centric work environment spans across our offices in Palo Alto, CA, and Seattle, WA, offering a unique blend of opportunities for professional growth and innovation. Key job responsibilities Collaborate with cross-functional teams to identify requirements for ML model development, focusing on enhancing mission understanding through innovative AI techniques, including retrieval-Augmented Generation or LLM in general. Design and implement scalable ML models capable of processing and analyzing large datasets to improve search and shopping experiences. Must have a strong background in machine learning, AI, or computational sciences. Lead the management and experiments of ML models at scale, applying advanced ML techniques to optimize science solution. Serve as a technical lead and liaison for ML projects, facilitating collaboration across teams and addressing technical challenges. Requires strong leadership and communication skills, with a PhD in Computer Science, Machine Learning, or a related field.

The Automated Reasoning Group in the AWS Neuron Compiler team is looking for an Applied Scientist to work on the intersection of Artificial Intelligence and program analysis to raise the code quality bar in our state-of-the-art deep learning compiler stack. This stack is designed to optimize application models across diverse domains, including Large Language and Vision, originating from leading frameworks such as PyTorch, TensorFlow, and JAX. Your role will involve working closely with our custom-built Machine Learning accelerators, Inferentia and Trainium, which represent the forefront of AWS innovation for advanced ML capabilities, and is the underpinning of Generative AI. In this role as an Applied Scientist, you'll be instrumental in designing, developing, and deploying analyzers for ML compiler stages and compiler IRs. You will architect and implement business-critical tooling, publish cutting-edge research, and mentor a brilliant team of experienced scientists and engineers. You will need to be technically capable, credible, and curious in your own right as a trusted AWS Neuron engineer, innovating on behalf of our customers. Your responsibilities will involve tackling crucial challenges alongside a talented engineering team, contributing to leading-edge design and research in compiler technology and deep-learning systems software. Strong experience in programming languages, compilers, program analyzers, and program synthesis engines will be a benefit in this role. A background in machine learning and AI accelerators is preferred but not required. A day in the life 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. 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. Within AWS UC, Amazon Dedicated Cloud (ADC) roles engage with AWS 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. 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. 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.

About Amazon Advertising: Amazon Advertising operates at the intersection of eCommerce and advertising, offering a rich array of digital display advertising solutions with the goal of helping our customers find and discover anything they want to buy. We help advertisers of all types to reach Amazon customers on Amazon.com, across our other owned and operated sites, on other high quality sites across the web, and on millions of mobile devices. We start with the customer and work backwards in everything we do, including advertising. If you’re interested in joining a rapidly growing team working to build a unique, world-class advertising group with a relentless focus on the customer, you’ve come to the right place. About our team: Our team, CreativeX optimizations, is responsible for tailoring the visual experience of ads to each context in real time. To accomplish this, we are investing in latent-diffusion models, large language models (LLM), reinforced learning (RL), Computer Vision, and related methods. Key job responsibilities We are looking for talented Applied Scientists who are adept at a variety of skills, especially with reinforcement learning and recommendations, and familiarity with LLMs, latent diffusion, or related foundational models that will accelerate our plans to dynamically optimize ad creatives on behalf of advertisers. Every member of the team is expected to build customer (advertiser) facing features, contribute to the collaborative spirit within the team, publish, patent, and bring cutting edge research to raise the bar within the team.

Advertising at Amazon is a fast-growing multi-billion dollar business that spans across desktop, mobile and connected devices; encompasses ads on Amazon and a vast network of hundreds of thousands of third party publishers; and extends across US, EU and an increasing number of international geographies. One of the key focus areas is Traffic Quality where we endeavour to identify non-human and invalid traffic within programmatic ad sources, and weed them out to ensure a high quality advertising marketplace. We do this by building machine learning and optimization algorithms that operate at scale, and leverage nuanced features about user, context, and creative engagement to determine the validity of traffic. The challenge is to stay one step ahead by investing in deep analytics and developing new algorithms that address emergent attack vectors in a structured and scalable fashion. We are committed to building a long-term traffic quality solution that encompasses all Amazon advertising channels and provides state-of-the-art traffic filtering that preserves advertiser trust and saves them hundreds of millions of dollars of wasted spend. We are looking for talented applied scientists who enjoy working on creative machine learning algorithms and thrive in a fast-paced, fun environment. An Applied Scientist is responsible for solving inherently hard problems in advertising fraud detection using deep learning, self-supervised techniques, representation learning and advanced clustering. An ideal candidate should have strong depth and breadth knowledge in machine learning, data mining and statistics. Traffic quality systems process billions of ad-impressions and clicks per day, by leveraging cutting-edge open source technologies like Hadoop, Spark, Redis and Amazon's cloud services like EC2, S3, EMR, DynamoDB and RedShift. The candidate should have reasonable programming and design skills to manipulate unstructured and big data and build prototypes that work on massive datasets. The candidate should be able to apply business knowledge to perform broad data analysis as a precursor to modeling and to provide valuable business intelligence.

The Amazon Search Mission Understanding (SMU) team is at the forefront of revolutionizing the online shopping experience through the Amazon search page. Our ambition extends beyond facilitating a seamless shopping journey; we are committed to creating the next generation of intelligent shopping assistants. Leveraging cutting-edge Large Language Models (LLMs), we aim to redefine navigation and decision-making in e-commerce by deeply understanding our users' shopping missions, preferences, and goals. By developing responsive and scalable solutions, we not only accomplish the shopping mission but also foster unparalleled trust among our customers. Through our advanced technology, we generate valuable insights, providing a guided navigation system into various search missions, ensuring a comprehensive and holistic shopping experience. Our dedication to continuous improvement through constant measurement and enhancement of the shopper experience is crucial, as we strategically navigate the balance between immediate results and long-term business growth. We are seeking an Applied Scientist who is not just adept in the theoretical aspects of Machine Learning (ML), Artificial Intelligence (AI), and Large Language Models (LLMs) but also possesses a pragmatic, hands-on approach to navigating the complexities of innovation. The ideal candidate will have a profound expertise in developing, deploying, and contributing to the next-generation shopping search engine, including but not limited to Retrieval-Augmented Generation (RAG) models, specifically tailored towards enhancing the Rufus application—an integral part of our mission to revolutionize shopping assistance. You will take the lead in conceptualizing, building, and launching groundbreaking models that significantly improve our understanding of and capabilities in enhancing the search experience. A successful applicant will display a comprehensive skill set across machine learning model development, implementation, and optimization. This includes a strong foundation in data management, software engineering best practices, and a keen awareness of the latest developments in distributed systems technology. We are looking for individuals who are determined, analytically rigorous, passionate about applied sciences, creative, and possess strong logical reasoning abilities. Join the Search Mission Understanding team, a group of pioneering ML scientists and engineers dedicated to building core ML models and developing the infrastructure for model innovation. As part of Amazon Search, you will experience the dynamic, innovative culture of a startup, backed by the extensive resources of Amazon.com (AMZN), a global leader in internet services. Our collaborative, customer-centric work environment spans across our offices in Palo Alto, CA, and Seattle, WA, offering a unique blend of opportunities for professional growth and innovation. Key job responsibilities Collaborate with cross-functional teams to identify requirements for ML model development, focusing on enhancing mission understanding through innovative AI techniques, including retrieval-Augmented Generation or LLM in general. Design and implement scalable ML models capable of processing and analyzing large datasets to improve search and shopping experiences. Must have a strong background in machine learning, AI, or computational sciences. Lead the management and experiments of ML models at scale, applying advanced ML techniques to optimize science solution. Serve as a technical lead and liaison for ML projects, facilitating collaboration across teams and addressing technical challenges. Requires strong leadership and communication skills, with a PhD in Computer Science, Machine Learning, or a related field.

Amazon's Global Logistics (GL) team is seeking an experienced Senior Applied Scientist to research and deploy production solutions for transportation Pricing, Downstream Impact (DSI), and Network Flow. In this role, you will contribute to our vision of offering best-in-class global transportation capabilities for FBA Sellers and Retail Vendors, enabling them to ship efficiently from their locations to Amazon warehouses worldwide. Your work will help lower the cost structure for Amazon and our shippers, while also improving selection and availability for Amazon's consumers by simplifying complex global supply chains and replenishing inventories faster. Key job responsibilities - Collaborate closely with product managers, research scientists, operations leaders, and technical leadership to build cutting-edge transportation capabilities. - Analyze large datasets, develop end-to-end workflows, prototype optimization and machine learning models, and launch production-ready solutions. - Communicate your research findings and provide scientific guidance to the business, influencing our product strategy and roadmap. - Conduct experimental research that will inform future investment areas for the transportation business. A day in the life - Reviewing and refining the requirements for a new transportation pricing model with the product management team. - Conducting exploratory data analysis to uncover insights that can inform the design of the pricing algorithm. - Building and testing optimization prototypes, iterating on the model based on performance metrics. - Presenting your progress and initial findings to senior leadership, soliciting feedback to shape the next phase of development. - Collaborating with the engineering team to ensure a smooth transition of the model into production. About the team You will be joining the Network Economics, Research and Data Science (NERDS) Team, which supports GL's transportation business for North America (United States, Canada, and Mexico). The team's research focuses on developing solutions to improve transportation pricing, costs, speed, shipper support, fraud/theft prevention, shipment visibility, and delivery appointment scheduling for Amazon warehouses. 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 Learn more about our benefits here: https://www.amazon.jobs/en/internal/benefits/us-benefits-and-stock

Amazon Devices is one of the most innovative and fastest growing businesses at Amazon. Within the Amazon Devices, the Pre-Owned business team owns the Trade-in experience, and manages the sales of a broad portfolio of pre-owned devices. We set big goals and are looking for people who can help us reach and exceed them. Do you want to work in a role where you are encouraged to build and have the autonomy to push boundaries? Do you love to see an immediate impact from your actions? The Devices team at Amazon is seeking a talented and experienced Segmentation Scientist to drive our new initiative, which aims to create a best-in-class trade-in and upgrade experience for Amazon Device customers. In this role, you will leverage science skills to plan and execute experiments, identify key customer segments, analyze results, and predict benefits. You'll work cross-functionally with product, marketing, and analytics teams to develop scientific targeting strategies to effectively reach various customer segments with personalized offers. You'll apply advanced data science techniques to solve complex business problems and directly impact the customer experience. Your work will help millions of customers access the latest innovations while driving business value. The ideal candidate will have strong analytical and communication skills, experience with experimental design and customer segmentation, and the ability to translate data into actionable insights. If you're passionate about using data to drive product strategy and customer experience, we'd love to talk to you about joining our team! Key job responsibilities - Design and plan upgrade experiments across product lines, customer segments, and multiple channels (e.g., email, gateway, on-device amongst other channels) - Develop customer segmentation models to identify high-value upgrade targets - Develop Propensity Models based on the experimentation - Analyze experiment results and customer behavior to uncover key insights - Build predictive models to forecast upgrade rates and program benefits - Partner with marketing teams to test, evaluate, and refine targeted messaging and optimal channel mix for different customer segments, with the goal of optimizing channel strategy, engagement, and conversion rates - Collaborate with product teams to refine the upgrade experience based on data insights - Present findings and recommendations to leadership to drive strategy This is an exciting opportunity to shape a major strategic initiative for Amazon Devices.

Are you excited by the idea of developing personalized experiences for Amazon customers as they shop? Are you looking for new challenges and to solve hard science problems while applying state-of-the-art recommendation system modeling techniques? Join us and you'll help millions of customers make informed purchase decisions while also advancing the state of Amazon's science by publishing research! Key job responsibilities - Participate in the design, development, evaluation, deployment and updating of data-driven models for shopping personalization. - Use expertise in supervised and uplift learning algorithms to improve ML performance - Research and implement novel ML and statistical approaches to add value to the business. - Design A/B tests and conduct statistical analysis on their results - Work with distributed machine learning and statistical algorithms to harness enormous volumes of data at scale to serve our customers - Work closely with internal stakeholders like the business teams, engineering teams and partner teams and align them with respect to your focus area - Present and publish science research, contributing to Amazon's science community - Mentor junior engineers and scientists. About the team Our team's mission is to surface the right payments-related recommendations to customers at the right time, helping create a rewarding and successful shopping experience for Amazon's customers. Our team's culture is highly collaborative, with an emphasis on supporting each other and learning from one another. We dedicate time each week to focus on personal development and expanding our knowledge as a team. We also highly value having a big impact, both for Amazon's business and for our customers.

Are you excited about developing cutting-edge generative AI, large language models (LLMs), and foundation models? Are you looking for opportunities to build and deploy them on real-world problems at a truly vast scale with global impact? As part of AFT (Amazon Fulfillment Technologies) AI, a group of over 50 scientists and engineers, we are on a mission to build a new generation of dynamic end-to-end prediction models (and agents) for our warehouses based on GenAI and LLMs. These models will be able to understand and make use of petabytes of human-centered as well as process information, and learn to perceive and act to further improve our world-class customer experience – at Amazon scale. We are looking for an Applied Scientist who will help us build next-level process prediction and shift simulations for all systems in a full warehouse with the help of generative AI, graph neural networks, and LLMs. Together, we will be pushing beyond the state of the art in simulation and optimization of one of the most complex systems in the world: Amazon's Fulfillment Network. Key job responsibilities In this role, you will dive deep into our fulfillment network, understand complex processes, and channel your insights to build large-scale machine learning models (LLMs and Transformer-based GNNs) that will be able to understand and predict the state and future of our buildings, network, and orders. You will face a high level of research ambiguity and problems that require creative, ambitious, and inventive solutions. You will work with and in a team of applied scientists to solve cutting-edge problems going beyond the published state of the art that will drive transformative change on a truly global scale. If you thrive in a dynamic environment and are passionate about pushing the boundaries of generative AI, LLMs, and optimization systems, we want to hear from you. A day in the life Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply! About the team Amazon Fulfillment Technologies (AFT) powers Amazon’s global fulfillment network. We invent and deliver software, hardware, and data science solutions that orchestrate processes, robots, machines, and people. We harmonize the physical and virtual world so Amazon customers can get what they want, when they want it. The AFT AI team has deep expertise developing cutting edge AI solutions at scale and successfully applying them to business problems in the Amazon Fulfillment Network. These solutions typically utilize machine learning and computer vision techniques, applied to text, sequences of events, images or video from existing or new hardware. We influence each stage of innovation from inception to deployment, developing a research plan, creating and testing prototype solutions, and shepherding the production versions to launch.

The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Senior Applied Scientist with a strong deep learning background, to help build industry-leading technology with Large Language Models (LLMs) and multimodal systems. Key job responsibilities As a Senior Applied Scientist with the AGI team, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art with LLMs. Your work will directly impact our customers in the form of products and services that make use of audio technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in AGI in speech/audio/music domains. About the team Our team has a mission to push the envelope of AGI in speech/audio/music domains, in order to provide the best-possible experience for our customers.