Careers

Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the limits. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. As an Applied Scientist on our team, you will focus on building state-of-the-art ML models for biology. Our team rewards curiosity while maintaining a laser-focus in bringing products to market. Competitive candidates are responsive, flexible, and able to succeed within an open, collaborative, entrepreneurial, startup-like environment. At the forefront of both academic and applied research in this product area, you have the opportunity to work together with a diverse and talented team of scientists, engineers, and product managers and collaborate with other teams.

The Amazon Web Services (AWS) Center for Quantum Computing (CQC) in Pasadena, CA, is looking to hire a Quantum Applied Scientist in the Test and Measurement group. You will be joining a multi-disciplinary team of scientists, engineers, and technicians, all working at the forefront of quantum computing to innovate for the benefit of our customers. You should have a deep and broad knowledge of experimental measurement techniques, and how to develop and automate them in software, towards improving the performance of quantum processors on the path towards delivering a fault-tolerant quantum computer. Key job responsibilities We are looking to hire an Applied Scientist focused on calibrating and optimizing the performance of integrated quantum processors. In this role, you will: - develop novel calibration and optimization routines - test and validate these experimental routines on processors hosted in a cryogenic environment - automate these routines to verify the expected performance of the processors at scale - contribute to novel quantum error correction demonstrations. You are expected to develop and lead high-impact research projects that intersect with our engineering roadmap. We are looking for candidates with strong engineering principles and resourcefulness. Organization and communication skills are essential. A day in the life As an Applied Scientist in the Test and Measurement group you characterize the integrated quantum processors designed and fabricated at CQC. To do so, you will: - collaborate with Software Development Engineers to develop and test novel calibration and optimization tools in software - work with System Engineers to set component level requirements as we scale processor complexity - work with quantum error correction (QEC) theorists to evaluate and improve the logical performance of these processors. 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. 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 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. Export Control Requirement: Due to applicable export control laws and regulations, candidates must be either a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum, or be able to obtain a US export license. If you are unsure if you meet these requirements, please apply and Amazon will review your application for eligibility.

Employer: Amazon.com Services LLC Position: Data Scientist II - AMZ27596.1 Location: Irving, TX Multiple Positions Available: Design and implement scalable and reliable approaches to support or automate decision making throughout the business. Apply a range of data science techniques and tools combined with subject matter expertise to solve difficult business problems and cases in which the solution approach is unclear. Acquire data by building the necessary SQL / ETL queries. Import processes through various company specific interfaces for accessing Oracle, RedShift, and Spark storage systems. Build relationships with stakeholders and counterparts. Analyze data for trends and input validity by inspecting univariate distributions, exploring bivariate relationships, constructing appropriate transformations, and tracking down the source and meaning of anomalies. Build models using statistical modeling, mathematical modeling, econometric modeling, network modeling, social network modeling, natural language processing, machine learning algorithms, genetic algorithms, and neural networks. Validate models against alternative approaches, expected and observed outcome, and other business defined key performance indicators. Implement models that comply with evaluations of the computational demands, accuracy, and reliability of the relevant ETL processes at various stages of production. (40 hours / week, 8:00am-5:00pm, Salary Range $141773 - $184000) Amazon.com is an Equal Opportunity – Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation #0000

Applied Scientists in AWS Science of Security are dedicated to making AWS the best computing service in the world for customers who require advanced and rigorous solutions for security, privacy, and sovereignty. Key job responsibilities The successful candidate will: * Solve large or significantly complex problems that require deep knowledge and understanding of your domain and scientific innovation. * Own the design, implementation, and delivery for solutions that have a long-term quantifiable impact. *Provide cross-organizational technical influence, increasing productivity and effectiveness by sharing your deep knowledge and experience. * Develop fundamentally new solutions for business problems. A day in the life This is a unique and rare opportunity to get in early on a fast-growing segment of AWS and help shape the technology, product and the business. You will have a chance to utilize your deep technical experience within a fast moving, start-up environment and make a large business and customer impact. About the team Diverse Experiences Amazon Security 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 Amazon Security? At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon’s products and services. We offer talented security professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores. Inclusive Team Culture In Amazon Security, it’s in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest security challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices. Training & 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, training, 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.

Do you want to define the scientific direction for how a global contact-center network forecasts demand, schedules its workforce, and optimizes operations in real time? The Eliza team within Amazon Connect (FCS) is looking for a Principal Research Scientist with a deep operations research specialization to set the research agenda in operations science — combinatorial optimization, queueing theory, stochastic modeling, and forecasting — and to translate that research into production systems that serve millions of customer interactions. As a Principal Research Scientist, you will be the senior technical voice for operations research across the org. You will identify the highest-leverage scientific problems, architect novel solutions, and drive them from research through production deployment. You will not sit apart from the work — you will remain deeply hands-on with data, models, and systems while raising the scientific bar for scientists and engineers around you. This is an individual-contributor Principal role: your influence comes from technical depth, invention, and the ability to move business and engineering roadmaps through scientific rigor. You will operate at the intersection of demand forecasting, workforce scheduling, and network optimization — applying combinatorial optimization to large-scale scheduling and resource-allocation problems and queueing theory to model contact-center dynamics under uncertainty, non-stationarity, and competing operational constraints at Internet scale — turning that reasoning into systems that continuously sense, predict, and optimize. Key job responsibilities - Set the multi-year research direction for operations research across contact-center demand prediction, workforce scheduling, and network optimization. - Design and deliver novel algorithms in combinatorial optimization (large-scale scheduling, resource allocation, integer/constraint programming) and queueing theory (contact-center modeling, staffing under stochastic arrivals), alongside stochastic modeling and time-series forecasting, that advance the state of the art while solving real operational problems. - Own end-to-end scientific solutions — from problem formulation and prototyping to production deployment — ensuring robustness, explainability, and seamless integration with existing systems. - Design rigorous experiments and evaluation methodology to validate hypotheses and quantify business impact; establish scientific-excellence mechanisms (metrics, benchmarks, peer review) that the broader science team adopts. - Partner with engineering, product, and operations teams to define data and logging requirements, get them prioritized on roadmaps, and translate scientific capabilities into measurable business outcomes. - Influence senior leadership through written papers and deep-dives, framing complex algorithmic trade-offs in clear business terms. - Mentor and raise the bar for applied and research scientists across the org while maintaining significant hands-on technical contribution. - Represent the team's science externally where appropriate (publications, patents, top-tier venues such as INFORMS, NeurIPS, ICML). A day in the life Your day blends hands-on science with technical leadership. You might spend the morning deep in data and models — prototyping a new combinatorial-optimization formulation for workforce scheduling or a queueing model for staffing under stochastic arrivals against production infrastructure — and the afternoon guiding fellow scientists through a hard optimization or stochastic-modeling problem, reviewing an experiment design, or aligning engineering partners on the data architecture needed to unlock the next capability. You'll drive technical discussions with the team and key stakeholders, and periodically write and present papers that shape the business and engineering roadmap.

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

MULTIPLE POSITIONS AVAILABLE Employer: AMAZON DEVELOPMENT CENTER U.S., INC. Offered Position: Applied Scientist III Job Location: New York, New York Job Number: AMZ10165497 Position Responsibilities: Participate in the design, development, evaluation, deployment and updating of data-driven models and analytical solutions for machine learning (ML) and/or natural language (NL) applications. Develop and/or apply statistical modeling techniques (e.g. Bayesian models and deep neural networks), optimization methods, and other ML techniques to different applications in business and engineering. Routinely build and deploy ML models on available data, and run and analyze experiments in a production environment. Identify new opportunities for research in order to meet business goals. Research and implement novel ML and statistical approaches to add value to the business. Mentor junior engineers and scientists. Position Requirements: Master’s degree or foreign equivalent degree in Computer Science, Machine Learning, Engineering, or a related field and two years of research or work experience in the job offered, or as a Research Scientist, Research Assistant, Software Engineer, or a related occupation. Employer will accept a Bachelor’s degree or foreign equivalent degree in Computer Science, Machine Learning, Engineering, or a related field and five years of progressive post-baccalaureate research or work experience in the job offered or a related occupation as equivalent to the Master’s degree and two years of research or work experience. Must have one year of research or work experience in the following skill(s): (1) programming in Java, C++, Python, or equivalent programming language; and (2) conducting the analysis and development of various supervised and unsupervised machine learning models for moderately complex projects in business, science, or engineering. Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation. 40 hours / week, 8:00am-5:00pm, Salary Range $183,800/year to $248,700/year. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, visit: https://www.aboutamazon.com/workplace/employee-benefits.#0000

The Sponsored Products and Brands (SPB) team at Amazon Ads is re-imagining the advertising landscape through state-of-the-art 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. Key job responsibilities This role will be pivotal in redesigning how ads contribute to a personalized, relevant, and inspirational shopping experience, with the customer value proposition at the forefront. Key responsibilities include, but are not limited to: - Contribute to the design and development of GenAI, deep learning, multi-objective optimization and/or reinforcement learning empowered solutions to transform ad retrieval, auctions, whole-page relevance, and/or bespoke shopping experiences. - Collaborate cross-functionally with other scientists, engineers, and product managers to bring scalable, production-ready science solutions to life. - Stay abreast of industry trends in GenAI, LLMs, and related disciplines, bringing fresh and innovative concepts, ideas, and prototypes to the organization. - Contribute to the enhancement of team’s scientific and technical rigor by identifying and implementing best-in-class algorithms, methodologies, and infrastructure that enable rapid experimentation and scaling. - Mentor and grow junior scientists and engineers, cultivating a high-performing, collaborative, and intellectually curious team. A day in the life As an Applied Scientist on the Sponsored Products and Brands Off-Search team, you will contribute to the development in Generative AI (GenAI) and Large Language Models (LLMs) to revolutionize our advertising flow, backend optimization, and frontend shopping experiences. This is a rare opportunity to redefine how ads are retrieved, allocated, and/or experienced—elevating them into personalized, contextually aware, and inspiring components of the customer journey. You will have the opportunity to fundamentally transform areas such as ad retrieval, ad allocation, whole-page relevance, and differentiated recommendations through the lens of GenAI. By building novel generative models grounded in both Amazon’s rich data and the world’s collective knowledge, your work will shape how customers engage with ads, discover products, and make purchasing decisions. If you are passionate about applying frontier AI to real-world problems with massive scale and impact, this is your opportunity to define the next chapter of advertising science. About the team The Off-Search team within Sponsored Products and Brands (SPB) is focused on building delightful ad experiences across various surfaces beyond Search on Amazon—such as product detail pages, the homepage, and store-in-store pages—to drive monetization. Our vision is to deliver highly personalized, context-aware advertising that adapts to individual shopper preferences, scales across diverse page types, remains relevant to seasonal and event-driven moments, and integrates seamlessly with organic recommendations such as new arrivals, basket-building content, and fast-delivery options. To execute this vision, we work in close partnership with Amazon Stores stakeholders to lead the expansion and growth of advertising across Amazon-owned and -operated pages beyond Search. We operate full stack—from backend ads-retail edge services, ads retrieval, and ad auctions to shopper-facing experiences—all designed to deliver meaningful value. Curious about our advertising solutions? Discover more about Sponsored Products and Sponsored Brands to see how we’re helping businesses grow on Amazon.com and beyond!

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.

Do you want to join a brand-new team building an AI system that would disrupt the industry? Do you enjoy dealing with ambiguity and working on hard problems in a fast-paced environment? Amazon Connect is a highly disruptive cloud-based contact center that enables businesses to deliver engaging, dynamic, and personal customer service experiences. With Amazon Connect, you can create your own cloud-based contact center and be taking calls in minutes. Amazon Connect leverages the power of Artificial Intelligence and the large ecosystem of AWS services such as Lex, Polly, Lambda, S3, and Kinesis to provide a truly frustration free and natural customer experience. With this technology, we are transforming an industry and the way customers interact with businesses and how agents service them. As a Data Scientist on our team, you will analyze data from massive data sets to categorize customer idiosyncrasies, identify outliers, and systematically detect anomalies that substantially affect the performance of our models. You will work closely with other senior technical leaders within the team and across AWS. You should know how to trace decisions in data from raw data through complex models to their impact business metrics. Experience with machine learning explainability is a plus. You should be able to translate well-defined business problems into data science problems and you solve these problems using appropriate assumptions, methodologies, and data science best practices. Our team is at an early stage, so you will have significant impact on our deliverables with no operational load from existing models/systems. We have a rapidly growing customer base and an exciting charter in front of us that includes solving highly complex engineering and algorithmic problems. We are looking for passionate, talented, and experienced people to join us to innovate on this new service that addresses customer needs to build modern contact centers in the cloud. The position represents a rare opportunity to be a part of a fast-growing business soon after launch, and help shape the technology and product as we grow. You will be playing a crucial role in developing the next generation contact center, and get the opportunity to design and deliver scalable, resilient systems while maintaining a constant customer focus. Learn more about Amazon Connect here: https://aws.amazon.com/connect/ Key job responsibilities Categorizing Customer Idiosyncrasies: As we expand to more customers, we are discovering that they use our product in very different ways and that poses issues for our models. Effectively summarizing these differences (for example, X% of customers do Y) would be immensely helpful. Detecting and Cleaning Up Outliers: We have situations where outliers have a huge impact on model outputs. You will help us develop mechanisms to clean up outliers for downstream consumption. Deep Diving Customer Issues: Customers have longstanding traditions and trusted formulas for managing their contact centers. When our formulas differ from theirs, we need to deep dive these discrepancies and determine if there is an issue with our model or if we are giving the customer better results than they are used to. Assessing Data Gaps: It's hard to estimate the weather in Seattle if the only data you have is the average weight of elephants in Zimbabwe. We know we don't have all the data we need, but we need to answer two related questions: (a) what features can we derive in creative ways from existing data sources? (b) can we estimate the benefit of getting a new data stream in terms of accuracy improvement? A day in the life Our team uses agile project management, so the DS calls in to our daily stand-up meeting in the morning to report status and explain their tasks for the day. Throughout the day, the DS will work with our product manager to discuss issues with our customers that require deep dives, work with our scientists to discuss model performance issues, and discuss software deliverables with our SDEs such as automation of data ingestion to save DS time, deployment of models, etc.