Careers

Alexa AI is looking for a Senior Applied Scientist to build Alexa+, Amazon's LLM-powered conversational assistant. You will work on key initiatives spanning large language model fine-tuning, alignment, agentic reasoning, and evaluation — directly shaping the experience for hundreds of millions of customers worldwide. As a Senior Applied Scientist, you are a strong technical contributor who independently drives complex projects from ideation to production. You design and run rigorous experiments, develop novel approaches to challenging problems, and deliver high-quality models and systems at scale. Your work is characterized by scientific rigor, engineering excellence, and a focus on measurable customer impact. You collaborate effectively across teams, contribute to scientific discussions and reviews, and help elevate the technical bar within the organization. You proactively identify opportunities, propose solutions, and influence technical direction within your project area. Basic Qualifications - PhD/MS in Computer Science, Electrical Engineering, Machine Learning, Natural Language Processing, or a related technical field, OR Master's degree with 5+ years of relevant industry experience - 3+ years of hands-on experience in applied machine learning, predictive modeling, or NLP - Strong programming skills in Python or a related language - Experience with deep learning frameworks (e.g., PyTorch, TensorFlow) - Track record of delivering ML/NLP solutions from research to production - Experience working with large language models (training, fine-tuning, or evaluation) Preferred Qualifications - 5+ years of relevant industry or academic research experience - Experience with LLM alignment techniques (RLHF, DPO, constitutional AI) - Experience with agentic AI systems, including planning, tool use, and orchestration - Experience with distributed training and large-scale model optimization - Peer-reviewed publications at top-tier venues (e.g., NeurIPS, ICML, ACL, EMNLP, ICLR) - Strong communication skills with the ability to present complex technical concepts to diverse audiences - Experience mentoring junior scientists or engineers Key job responsibilities - Design, implement, and evaluate novel approaches to LLM fine-tuning, alignment (RLHF, DPO), and distillation for production deployment - Develop and improve agentic systems — including multi-step reasoning, tool use, planning, and orchestration — that work reliably at scale - Build evaluation frameworks and methodologies that go beyond standard benchmarks to capture real-world conversational quality - Translate research advances into customer-facing products, working closely with engineering, product, and cross-functional science teams - Analyze large-scale experimental results, identify patterns, and iterate rapidly on model improvements - Publish results at top-tier venues and contribute to Amazon's presence in the broader research community - Mentor junior scientists and contribute to hiring efforts About the team Alexa AI is building the science and technology behind Alexa+, Amazon's next-generation conversational assistant. Our team works at the intersection of large language models, reinforcement learning from human feedback and verifiable rewards, agentic architectures, and multilingual/multimodal understanding. We operate at massive scale — our models serve customers across dozens of languages and device types. If you want to push the frontier of conversational AI and see your work used by people every day, come join us.

Have you ever ordered a product on Amazon and when that box with the smile arrived, wondered how it got to you so fast? Wondered where it came from and how much it cost Amazon? If so, the Amazon Global Supply Chain Optimization Technology (SCOT) organization is for you. Watch this video to learn more about our organization, SCOT: http://bit.ly/amazon-scot We are the Optimal Sourcing Systems team (OSS) within SCOT and are looking for a Senior Applied Scientist to join us! OSS designs and builds systems that measure and manage Amazon’s supplier capabilities, identify and react to supply disruptions, and prioritizes inbound freight for our global network. OSS software is used by every country Amazon services, and is a critical link to ensuring Amazon offers the products our customers want, at the lowest possible cost. This team under OSS orchestrates and tracks inventory movement into Amazon's network, maintains performance feedback loops, and ensures vendor compliance. The Senior Applied Scientist, in partnership with the Product Management and Tech teams, will lead efforts in following areas: 1) Provide technical leadership and mentorship to the Science team, setting the standard for methodological rigor, peer review, and innovation across all workstreams 2) Build solutions to enable collaborative inventory planning with vendors through agent to agent collaboration or humans-in-the loop collaborative methods 3) Pioneer Gen AI solutions for dispute evaluation and vendor coaching, defining the technical approach, evaluating model performance against business outcomes, and establishing responsible AI guardrails for production deployment 4) Drive the full development cycle from whiteboarding new algorithmic approaches to production-scale deployments 5) Collaborate with SDEs to build high-performance, distributed training and inference pipelines; translate complex scientific concepts into scalable, production-grade code The ideal candidate is a seasoned scientist who thrives in ambiguous, high-impact problem spaces and brings the technical depth to independently structure and solve complex challenges across the supply chain. The successful candidate will be a person who has deep understanding about machine learning/reinforcement learning/GenAI models, enjoys and excels at diving into data to analyze root causes, and implementing long term solutions. They can translate complex business logic into scalable models and communicate insights effectively to both technical and non-technical stakeholders. Keys to success in this role include exceptional Science depth and breadth, analytics, statistics, judgment, and communication skills. Experience with supply chain optimization, operations research, or vendor management systems is a plus. Key job responsibilities Set the technical vision and drive best practices for the team's science solutions, including model evaluation frameworks, experimentation standards, code quality, and documentation Mentor junior scientists and raise the bar across the organization Lead cross-functional collaboration with product managers, science, and engineering teams to define problem frameworks, identify high-impact opportunities, and architect end-to-end model solutions for Sourcing Execution & Performance systems Design and execute rigorous studies and predictive modeling pipelines on large-scale datasets and experiments, establishing methodological standards for statistical validity, reproducibility, and business interpretability Partner with engineering to productionize science workflows driving the automation of analysis processes, building scalable measurement solutions, and ensuring models are robust, monitored, and maintainable in production environments

Are you interested in how to build AI reasoning systems that give provably correct answers? Are you excited by science at the interface of classical AI reasoning and Large Language Models (LLMs)? Would you like to apply your technology to serve operations customers better? Amazon Robotics is looking for a talented Applied Scientist. You will innovate on combining language models (LMs) with classical AI reasoning. You will work with a team of scientists and engineers to achieve this. You will publish your results in papers at leading venues in AI. You will be part of a larger team and have the opportunity to work on problems such as: using LMs to generate plans, using AI reasoning to verify plan correctness, learning efficient reasoning strategies, self-improving models. You will work on basic science and on business problems in robotics, automation and fulfillment across our operations. Key job responsibilities In this role you will: • Work closely with other scientists and engineers, and be part of Amazon’s diverse global science community. • Publish your research in top-tier academic venues and hone your presentation skills. • Be inspired by challenges and opportunities to invent new techniques in your area(s) of expertise. A day in the life You'll meet regularly with your technical lead and your team on your ideas, get guidance and feedback, work together on architectures and algorithms, author papers, build AI systems, all with the aim of delivering results for your operations customers. You'll work closely with other scientists to review your plans and results. You'll meet with engineers to implement your ideas at scale. About the team The Veritas team is a science team working at the boundary between language models and classical AI reasoning. We work across on customer problems in fulfillment, automation and robotics. We focus on high quality research science informed by practical problems.

Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video technologist, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! Prime Video is disrupting traditional media with an ever-increasing selection of movies, TV shows, Emmy Award-winning original content, add-on subscriptions, and live events like Thursday Night Football. Within this expanding ecosystem, Linear TV with its 24/7 scheduled broadcast-style programming has emerged as one of our fastest-growing segments, with viewership hours increasing significantly year over year. This growth demonstrates that even in the streaming era, customers deeply value the lean-back, curated experience that Linear TV provides. Key job responsibilities As an Applied Scientist on LPEX, you will be a technical owner and science leader across the following areas: * Design, develop, and deploy machine learning models for content recommendation, viewer engagement optimization, and real-time personalization at the scale of hundreds of millions of Prime Video customers. * Own the complete ML lifecycle: problem formulation, data analysis, feature engineering, model development, offline and online evaluation, and reliable production deployment. * Build and continuously optimize recommendation systems with strict real-time latency requirements, ensuring that personalization decisions are delivered at speed and scale. * Design and execute rigorous A/B and multivariate experiments to measure recommendation quality, understand causal drivers of engagement, and iterate rapidly toward customer impact. * Partner with software engineering teams to productionize ML models, defining requirements for serving infrastructure, data pipelines, and model monitoring and observability. * Collaborate with product managers and cross-functional stakeholders to translate ambiguous business problems into well-scoped, tractable science solutions. * Mentor scientists and engineers on the team, setting a high bar for scientific rigor, experimental discipline, and ML engineering best practices. A day in the life We are looking for an Applied Scientist who will own the end-to-end machine learning lifecycle from problem formulation and research through experimentation and production deployment, building systems that help millions of customers discover the right content at the right time. It's Day 1 for personalizing the linear TV experience on Prime Video, and you will be at the forefront of this innovation. About the team The Linear Personalization Experience (LPEX) team is building next-generation, AI-powered personalization and recommendation systems to enhance this natural engagement and deliver a best-in-class Linear TV experience for Prime Video customers worldwide. The LPEX team's vision is to surface the breadth and depth of Prime Video's linear selection at exactly the right moment for each customer curating the most relevant programming, tailored to individual tastes, purchase behaviors, schedules, and viewing habits, while simultaneously elevating awareness of our extensive live and linear catalog. Our mission is to anticipate and exceed viewers' expectations, fostering deeper connections with the content they love. We adapt to viewers' preferences and propensities for both live and on-demand viewing, enriching the overall entertainment journey. The team operates at the intersection of machine learning research, large-scale distributed systems, and consumer product strategy, partnering closely with product management, engineering, and business development.

About Sponsored Products and Brands The Sponsored Products and Brands (SPB) team at Amazon Ads is re-imagining the advertising landscape through 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. About our team SPB Ad Response Prediction team is your choice, if you want to join a highly motivated, collaborative, and fun-loving team with a strong entrepreneurial spirit and bias for action. We are seeking an experienced and motivated Applied Scientist with machine learning engineering background who loves to innovate at the intersection of customer experience, deep learning, and high-scale machine learning systems. We are looking for a talented Applied Scientist with a strong background in machine learning engineering to join our team and help us grow the business. In this role, you will partner with a team of engineers and scientists to build advanced machine learning models and infrastructure, from training to inference, including emerging LLM-based systems, that deliver highly relevant ads to shoppers across all Amazon platforms and surfaces worldwide. Key job responsibilities As an Applied Scientist, you will: * Develop scalable and effective machine learning models and optimization strategies to solve business problems. * Conduct research on new machine learning modeling to optimize all aspects of Sponsored Products business. * Enhance the scalability, automation, and efficiency of large-scale training and real-time inference systems. * Pioneer the development of LLM inference infrastructure to support next-generation GenAI workloads at Amazon Ads scale.

We are seeking a Applied Scientist to join the Alexa AI PAPI (Personalization, Autonomy, and Proactive Intelligence) Science team. In this role, you will architect and scale next-generation memory intelligence and personalization capabilities that power Alexa Plus—enabling it to learn, memorize, reason, and deliver deeply personalized, useful, and delightful responses that approach the vision of a true general personal assistant. Your responsibilities include: * Advance core technology: Invent, design, and implement state-of-the-art solutions for previously unsolved problems in agentic AI, memory retrieval, and context management at scale. * Solve real customer problems: Build systems that learn from heterogeneous, multi-modal customer signals—conversations, device visual signals, ambient activities, purchase histories, and more—to deliver the right information, in the right format, at the right time. * Build for scalability: Design and deploy customer-feedback-driven, self-optimizing agentic architectures that serve millions of customers across Amazon surfaces, programs, and marketplaces. * Drive platform-level impact: Contribute to a platform science team responsible for organizing and reasoning over diverse customer interactions to continuously improve personalization quality. * Champion scientific rigor and responsible evaluation: Own the end-to-end science lifecycle—from hypothesis formulation and offline experimentation to online A/B testing and production accountability. Design evaluation that measure personalization quality and safety at scale, ensuring every launch is backed by statistically sound evidence. This is not incremental work. You will push the boundaries of what personalized AI assistants can do—bridging research in generative AI, memory systems, and agentic reasoning with production systems that operate at Amazon on scale. Your innovations will directly shape how millions of customers experience Alexa Plus daily.

Amazon.com’s Product Detail Page team is looking for talented, motivated and passionate applied scientist to be part of the design and development of a highly scalable multi-tiered shopping application to provide the best possible online shopping experience for Amazon customers world-wide. Our team is comprised of talented applied scientists, developers, testers, program managers, designers and product managers tasked with the singular goal to create THE world's best buying experience. Scientists on this team develop the next-generation technologies and experiences that change how millions interact and shop online. To provide the best possible online shopping at the scale of the web requires ideas from every area of computer science, including distributed computing, large-scale system design, machine learning, natural language processing, data compression and user interface design; the list goes on and is growing every day. We need our scientists to be versatile and always eager to tackle new problems as we continue to push technology forward. Our team leverages sophisticated econometric, machine learning, and big data technologies to help customers to discover the right products at the right prices from millions of trusted sellers billions of times a day. If you are looking for a career-defining opportunity on one of the most customer centric and business impacting teams within Amazon, we’d love to hear from you. We are looking for an Applied Scientist to help build the next generation of Detail Page optimization algorithms. These new set of algorithms will incorporate the continually changing preferences of our customers and continue to scale with numerous new programs that Amazon is introducing for our customers. You will work with multiple Amazon businesses and programs to identify big business opportunities and propose new business features and technical systems to improve customer experience on Amazon Detail Page, Search Page and many other widgets throughout the website. You will be responsible for the quality of algorithm design and will get the opportunity to present your ideas and share results of your deliverables with Amazon executives on a frequent basis. You will get an opportunity to work with senior scientists to define and enforce broad, company-wide technical standards in optimization techniques, statistical modeling and simulation techniques, and/or data analytics.

Amazon Customer Service (CS) Data Intelligence builds the data and Artificial Intelligence (AI) foundations for CS to ensure Amazon delivers the best customer service possible. CS Economics sits within CS DI and contributes to the CS knowledge base and decision frameworks. CS Economics seeks economists to apply economic methods to solve business problems. The ideal candidate will work with engineers and applied scientists to design models that leverage large scale and unstructured data, design scalable agents for non-tech CS partners to understand the impact of their actions, and propose mechanism designs to robustly match customers to our services. CS Economics is looking for optimistic critical-thinkers who combine a strong technical economic toolbox with a desire to learn from other disciplines, and who know how to execute and deliver on big ideas as part of an interdisciplinary technical team. Ideal candidates enjoy working in a team setting with individuals from diverse disciplines and backgrounds. They will work with teammates to develop scientific models and conduct data analysis, modeling, and experimentation that is necessary for estimating and validating models. They will work closely with engineering teams to develop scalable data resources to support rapid insights, and take successful models and findings into production as new products and services. They will be customer-centric and will communicate scientific approaches and findings to business leaders, listening to and incorporate their feedback, and delivering successful scientific solutions. Key job responsibilities - Design and conduct rigorous evaluations of CS actions - Develop experiments to evaluate product launches - 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, e.g., identify the appropriate research question and identification strategy, write code to estimate heterogeneous treatment effects or conduct experiment analysis, write and present a document with findings to business leaders. We collaborate with partner teams within and outside of CS throughout the process, from understanding their challenges, to developing a research agenda that will address those challenges, to help them implement solutions. About the team Amazon Customer Service (CS) Economics provides estimates and measures of the causal impact of CS actions on costs and benefits. We build agents and guide leadership to establish processes to scale valid experimentation, causal inference, and mechanism design.

Amazon's Search team creates ML algorithms that connect customers around the world with products that delight them. We harness machine learning 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 As an Applied Scientist on the Search Ranking team, you will build search ranking models that work for thousands of product types, billions of queries, and hundreds of millions of customers spread around the world. You will find the next set of big improvements to ranking, leverage large datasets to understand the complexities of customer behavior, and build ML models that work at Amazon scale. Amazon's Search ranking relies on efficient early stage ranking followed by power final stage ranking models. this role will focus on developing efficient models and exploration techniques to optimize the early stage ranking phase. 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 collaborating with partner teams on joint goals. 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 span machine learning for better ranking, reinforcement learning to bring the benefits of exploration to search ranking, and infrastructure to make it all happen at scale and efficiently.

At Amazon, we are working to be the most customer-centric company on earth, where customers can find and discover anything they might want to buy online. Our Supply Chain organization spans the entire Amazon fulfillment network, from inventory placement and capacity planning through middle mile and last mile delivery. Our goal is to build a world class, end-to-end supply chain that exceeds the expectations of our customers by ensuring their orders are delivered as quickly, accurately, and cost effectively as possible. We are now looking to hire a passionate, innovative and customer-obsessed candidate to support our end-to-end network planning and optimization across the Amazon supply chain. As an Applied Scientist, you will work with software engineers, product managers and business teams to understand the requirements and current challenges, distill that understanding to elegantly define the problem, and develop innovative solutions that integrate planning and execution across the entire fulfillment pipe. A central part of this mission is harnessing recent advances in Artificial Intelligence, including machine learning, large language models, and generative AI, to transform how we optimize the network and make decisions at scale. Key job responsibilities • Solve complex optimization and machine learning problems using scalable algorithmic techniques. • Apply modern AI methods, including generative and foundation models, to improve optimization, forecasting, and automated decision making across the supply chain. • Design and develop efficient research prototypes that address real-world problems across Amazon's end-to-end supply chain operations. • Lead complex time-bound, long-term as well as ad-hoc analyses to assist decision making. • Communicate to leadership results from business analysis, strategies and tactics, including how AI-driven approaches change the way decisions are made. A day in the life The role will own the approval from senior functional leaders to enable strategies that improve processes and performance across the supply chain. You will be a natural self-starter who is comfortable supporting complex cross functional projects and action plans. You will have a true hands-on approach, the ability to generate solutions, strong process management skills, and be an effective communicator.