Austin

Research in Austin, the Texas state capital, spans several efforts at Amazon, including retail supply chain optimization, transportation management, and technology related to Amazon consumer electronics such as Ring and Blink. Teams in Austin also work on science for middle-mile planning and optimization.

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A view of the large building surrounded by trees in Austin, TX

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— Austin office building

Located in Austin's North Burnet neighborhood, the office is near two major local highways, so commuting is easy. Public transportation is also accessible.

An angled view of the building's main entrance in Austin, TX, featuring the building's numbers

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— Austin office building

Close to shopping and dining, and not too far from downtown, this location offers amenities such as a mother's room and an interfaith prayer room.

A view of the outdoor green space, trees, and stone benches behind the office building in Austin, TX

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— Austin office building

The bicycle storage cage is located on the north side first floor of the parking garage.

Research areas

Scientists in the Austin area are conducting research across many disciplines, including data science, operations research, supply chain management, and transportation logistics.

Working in Austin

Amazon provides scientists room to take risks and fail; a community for collaboration and support for continued learning; and the opportunity to have an impact at global scale. Scientists are encouraged to engage with the research community in many forms, from attending conferences and writing research papers, to contributing to open-source code, and public datasets.

Unlike many major cities, Austin's skyline isn't dominated by skyscrapers. This is largely due to a restriction preserving the view of the state capitol building from various locations. With its famed music scene and annual hosting of the South by Southwest music and interactive festival, Austin has become dubbed the “Silicon Hills.”

Collaborations

Our Austin scientists collaborate with universities and other institutions around the globe. To see a summary of some of Amazon’s scientific collaborations, visit our academic collaborations page.

Open listings

Amazon ranked second on the 2024 list of the best large workplaces to grow your career in the US. Visit our careers page to see all open science roles, both in the US and around the world.

Principal Applied Scientist, International Machine Learning

IN, KA, Bengaluru

Do you want to join an innovative team of scientists who use machine learning and statistical techniques to create state-of-the-art solutions for providing better value to Amazon’s customers? Do you want to build and deploy advanced algorithmic systems that help optimize millions of transactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data to solve real world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Machine Learning and Data Sciences team for India Consumer Businesses. If you have an entrepreneurial spirit, know how to deliver, love to work with data, are deeply technical, highly innovative and long for the opportunity to build solutions to challenging problems that directly impact the company's bottom-line, we want to talk to you. Major responsibilities - Use machine learning and analytical techniques to create scalable solutions for business problems - Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes - Design, development, evaluate and deploy innovative and highly scalable models for predictive learning - Research and implement novel machine learning and statistical approaches - Work closely with software engineering teams to drive real-time model implementations and new feature creations - Work closely with business owners and operations staff to optimize various business operations - Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation - Mentor other scientists and engineers in the use of ML techniques

Applied Scientist, Optimal Sourcing Systems

US, NY, New York

Amazon is looking for a Senior Applied Scientist to help build the next generation of sourcing and vendor experience systems. The Optimal Sourcing Systems (OSS) owns the optimization of inventory sourcing and the orchestration of inbound flows from vendors worldwide. We source inventory from thousands of vendors for millions of products globally while orchestrating the inbound flow for billions of units. Our goals are to increase reliable access to supply, improve supply chain-driven vendor experience, and reduce end-to-end supply chain costs, all in service of maximizing Long-Term Free Cash Flow (LTFCF) for Amazon. As a Senior Applied Scientist, you will work with software engineers, product managers, and business teams to understand the business problems and requirements, distill that understanding to crisply define the problem, and design and develop innovative solutions to address them. Our team is highly cross-functional and employs a wide array of scientific tools and techniques to solve key challenges, including optimization, causal inference, and machine learning/deep learning. Some critical research areas in our space include modeling buying decisions under high uncertainty, vendors' behavior and incentives, supply risk and enhancing visibility and reliability of inbound signals. Key job responsibilities You will be a science tech leader for the team. As a Applied Scientist you will: - Set the scientific strategic vision for the team. You - - lead the decomposition of problems and development of roadmaps to execute on it. - Set an example for other scientists with exemplary scientific analyses; maintainable, extensible, and well-tested code; and simple, intuitive, and effective solutions. - Influence team business and engineering strategies. - Exercise sound judgment to prioritize between short-term vs. long-term and business vs. technology needs. - Communicate clearly and effectively with stakeholders to drive alignment and build consensus on key initiatives. - Foster collaborations between scientists across Amazon researching similar or related problems. - Actively engage in the development of others, both within and outside the team. - Engage with the broader scientific community through presentations, publications, and patents.

Applied Scientist, Last Mile

US, WA, Bellevue

Amazon’s Last Mile Team is looking for a passionate individual with strong optimization and analytical skills to join its Last Mile Science team in the endeavor of designing and improving the most complex planning of delivery network in the world. Last Mile builds global solutions that enable Amazon to attract an elastic supply of drivers, companies, and assets needed to deliver Amazon's and other shippers' volumes at the lowest cost and with the best customer delivery experience. Last Mile Science team owns the core decision models in the space of jurisdiction planning, delivery channel and modes network design, capacity planning for on the road and at delivery stations, routing inputs estimation and optimization. Our research has direct impact on customer experience, driver and station associate experience, Delivery Service Partner (DSP)’s success and the sustainable growth of Amazon. Optimizing the last mile delivery requires deep understanding of transportation, supply chain management, pricing strategies and forecasting. Only through innovative and strategic thinking, we will make the right capital investments in technology, assets and infrastructures that allows for long-term success. Our team members have an opportunity to be on the forefront of supply chain thought leadership by working on some of the most difficult problems in the industry with some of the best product managers, scientists, and software engineers in the industry. Key job responsibilities Candidates will be responsible for developing solutions to better manage and optimize delivery capacity in the last mile network. The successful candidate should have solid research experience in one or more technical areas of Operations Research or Machine Learning. These positions will focus on identifying and analyzing opportunities to improve existing algorithms and also on optimizing the system policies across the management of external delivery service providers and internal planning strategies. They require superior logical thinkers who are able to quickly approach large ambiguous problems, turn high-level business requirements into mathematical models, identify the right solution approach, and contribute to the software development for production systems. To support their proposals, candidates should be able to independently mine and analyze data, and be able to use any necessary programming and statistical analysis software to do so. Successful candidates must thrive in fast-paced environments, which encourage collaborative and creative problem solving, be able to measure and estimate risks, constructively critique peer research, and align research focuses with the Amazon's strategic needs.

Applied Scientist , Amazon

US, CA, Palo Alto

We’re working to improve shopping on Amazon using the conversational capabilities of large language models, and are searching for pioneers who are passionate about technology, innovation, and customer experience, and are ready to make a lasting impact on the industry. You’ll be working with talented scientists, engineers, and technical program managers (TPM) to innovate on behalf of our customers. If you’re fired up about being part of a dynamic, driven team, then this is your moment to join us on this exciting journey!

Senior Applied Scientist, Sponsored Products

US, NY, New York

Amazon is investing heavily in building a world class advertising business and developing a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses for driving long-term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities. Sponsored Products DP Experience and Market place org is looking for a strong Senior Applied Scientist who has a track-record of performing deep analysis and is passionate about applying advanced ML and statistical techniques to solve real-world, ambiguous and complex challenges to optimize and improve the product performance, and who is motivated to achieve results in a fast-paced environment. The position offers an exceptional opportunity to grow your technical and non-technical skills and make a real difference to the Amazon Advertising business. As a Senior Applied Scientist on this team, you will: * Be the technical leader in Machine Learning; lead efforts within this team and collaborate across teams * Rapidly design, prototype and test many possible hypotheses in a high-ambiguity environment, perform hands-on analysis and modeling of enormous data sets to develop insights that improve shopper experiences and merchandise sales * Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity. * Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models. * Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving. * Research new and innovative machine learning approaches. * Promote the culture of experimentation and applied science at Amazon About the team Sponsored Products (SP) is Amazon's largest and fastest growing business. Over the last few years we grown to a multi-billion dollar business. SP ads are shown prominently throughout search and detail pages, allowing shoppers to seamlessly discover products sold on Amazon. Ad experience and market place is one of the highest impact decisions we make. This role has unparalleled opportunity to grow our marketplace and deliver value for advertisers and shoppers. You will invent new experiences and influence customer-facing shopping experiences; this is your opportunity to work within the fastest-growing businesses across all of Amazon!

Principal Scientist, Kuiper Capacity Planning - Simulation & Optimization

US, WA, Redmond

Project Kuiper is an initiative to increase global broadband access through a constellation of 3,236 satellites in low Earth orbit (LEO). Its mission is to bring fast, affordable broadband to unserved and underserved communities around the world. Project Kuiper will help close the digital divide by delivering fast, affordable broadband to a wide range of customers, including consumers, businesses, government agencies, and other organizations operating in places without reliable connectivity. The Kuiper Global Capacity Planning team owns designing, implementing, and operating systems that support the planning, management, and optimization of Kuiper network resources worldwide. We are looking for a talented principal scientist to lead Kuiper’s long-term vision and strategy for capacity simulations and inventory optimization. This effort will be instrumental in helping Kuiper execute on its business plans globally. As one of our valued team members, you will be obsessed with matching our standards for operational excellence with a relentless focus on delivering results. Key job responsibilities In this role, you will: Work cross-functionally with product, business development, and various technical teams (engineering, science, R&D, simulations, etc.) to establish the long-term vision, strategy, and architecture for capacity simulations and inventory optimization. Design and deliver modern, flexible, scalable solutions to complex optimization problems for operating and planning satellite resources. Lead short and long terms technical roadmap definition efforts to predict future inventory availability and key operational and financial metrics across the network. Design and deliver systems that can keep up with the rapid pace of optimization improvements and simulating how they interact with each other. Analyze large amounts of satellite and business data to identify simulation and optimization opportunities. Synthesize and communicate insights and recommendations to audiences of varying levels of technical sophistication to drive change across Kuiper. Export Control Requirement: Due to applicable export control laws and regulations, candidates must be 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.

Sr. Applied Scientist - Global Operational Excellence, GOX DEA

GB, London

Disrupting the way Amazon fulfills our customers’ orders. Amazon operations is changing the way we improve Customer Experience through flawless fulfillment focused on 1) successful on-time delivery, 2) at speed and 3) at the lowest possible cost. Being the engine of Amazon Operational excellence, driving zero defects through ideal operation, being the heart of the Fulfillment network and its center of excellence, being proactive and aspiring for zero defects across the network with 100% organizational engagement. For example, our applied science team leverage a variety of advanced machine learning and cloud computing techniques to power Amazon's operations performance management. This includes building algorithms and cloud services using LLMs, deep neural networks, and other ML approaches to make root cause analysis of incidents and defects better. They develop machine learning models to predict inbound capacity forecasts and select the optimal order of unloading and stowing the incoming items in the Fulfilment Center. The teams also utilize Langchain, Amazon Bedrock, Amazon Textract, ElasticCache Redis, Opensearch and Kubernetes to extract insights from big data and deliver recommendations to operations managers, continuously improving through offline analysis and impact evaluation. Underpinning these efforts are unique technical challenges, such as operating at unprecedented scale (100k requests per second with SNS/SQS and <1ms latency with Redis) while respecting privacy and customer trust guarantees, and solving a wide variety of complex computational operational problems related to inbound management for unloading and stowing before stow time SLA, outbound for picking and packing before SLAM PAD time and shipping for staging and loading before Critical Pull Time. Key job responsibilities GOX team is looking for a Senior Applied Scientist to support our vision of giving our customers the best fulfillment experience in the world, and our mission of delighting our customers by providing capabilities, tools and mechanisms to fulfillment operations. As Skynet Sr. APSCI, you would be providing resources and expertise for all data related reports (dashboard, scorecards…), analysis (statistical approach), and Machine Learning products and tools development. On top of your internal customers within GOX team you would be supporting more widely with your experience and skills all across the org, partnering with a wide range of departments within Ops Integration (Packaging, Sustainability) within the company mainly with ICQA, ATS, AMZL, GTS… on several projects. You will be part of the community of Scientists within Amazon Operations including other AS, BIEs, SDEs, … split across the different departments. You will be part of projects requiring your close collaboration and interactions with Operations that require you to have a good understanding of product flow and process all along the distribution chain. The GOX team is now recognized for its expertise and excellence in creating tools that improve massively the customer experience. Several of them now rolled out in other regions with some of these tools becoming worldwide standard. Reporting to the GOX Senior Manager, you will be responsible for developing the data-driven decision process from historical data and ML based predictive analysis and maintaining accurate and reliable data infrastructure. You will work across the entire business, and be exposed to a wide range of functions from Operations, Finance, Technology, and Change management. The successful candidate will be able to work with minimal instruction and oversight, manage multiple tasks and support projects simultaneously. Maintaining your relationships with the customers in operations and within the team, while owning deliverables end-to-end is expected. Critical to the success of this role is your ability to work with big data, develop insightful analysis, communicate findings in a clear and compelling way and work effectively as part of the team, raising the bar and insisting on high standards. About the team GOX DEA team is the engine of Amazon Operational excellence at the heart of the fulfillment network operations, aspiring zero defects. It is our purpose to improve Customer Experience through flawless fulfillment focused on 1) successful on-time delivery, 2) at speed and 3) at the lowest possible cost. Our Solutions support on-time delivery of billions of packages to our customers across the globe leveraging AI & Generative AI technology.

Applied Scientist, AGI - Web & Knowledge Services

US, CA, Sunnyvale

Amazon's AGI Web & Knowledge Services group is seeking a passionate, talented, and inventive Applied Scientist to lead the development of industry-leading Information retrieval systems. As part of our cutting-edge AGI-IR team, you will play a pivotal role in developing efficient AI solutions for a multi-modal future at scale. In this role, you will work alongside renowned researchers and engineers to enable our customers to seamlessly interact with unstructured and semi-structured content through advanced capabilities like question answering, contextual search, and multi-turn dialogues. Your work will directly impact our customers in the form of products and services that make use of various machine learning, deep learning and language model technologies. Key job responsibilities - As an Applied Scientist, you will leverage your technical expertise and experience to demonstrate leadership in tackling large complex problems, setting the direction and collaborating with applied scientists and engineers to develop novel algorithms and modeling techniques to enable timely, relevant and delightful conversations. - Leverage Amazon's large-scale data and computing resources to accelerate advances in the state of the art. - Work backwards from customer needs and use that information to make trade-offs between different modeling approaches - Collaborate with software engineering teams to integrate successful experimental results into complex Amazon production systems - Report results to technical and business audiences in a manner that is statistically rigorous and compellingly relevant, exemplifying good scientific practice in a business environment - Drive best practices, helping to set high scientific and engineering standards on the team - Promote the culture of experimentation and applied science at Amazon

Applied Scientist

US, WA, Seattle

Do you want to join an innovative team of scientists who use machine learning and statistical techniques to help Amazon provide the best customer experience by protecting Amazon customers from hackers and bad actors? Do you want to build advanced algorithmic systems that help manage the trust and safety of millions of customer every day? Are you excited by the prospect of analyzing and modeling terabytes of data and create state-of-art algorithms to solve real world problems? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Amazon Account Integrity team. The Amazon Account Integrity team works to ensure that customers are protected from bad actors trying to access their accounts. Our greatest challenge is protecting customer trust without unjustly harming good customers. To strike the right balance, we invest in mechanisms which allow us to accurately identify and mitigate risk, and to quickly correct and learn from our mistakes. This strategy includes continuously evolving enforcement policies, iterating our Machine Learning risk models, and exercising high‐judgement decision‐making where we cannot apply automation. Main responsibilities - Use statistical and machine learning techniques to create scalable risk management systems - Analyzing and understanding large amounts of Amazon’s historical business data for specific instances of risk or broader risk trends - Design, development and evaluation of highly innovative models for risk management - Working closely with software engineering teams to drive real-time model implementations and new feature creations - Working closely with operations staff to optimize risk management operations - Establishing scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation - Tracking general business activity and providing clear, compelling management reporting on a regular basis - Research and implement novel machine learning and statistical approaches

Data Scientist, Generative AI Innovation Center

US, VA, Herndon

Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply cutting edge Generative AI algorithms to solve real world problems with significant impact? The Generative AI Innovation Center at AWS is a new strategic team that helps AWS customers implement Generative AI solutions and realize transformational business opportunities. This is a team of strategists, data scientists, engineers, and solution architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI. The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, select and train and fine tune the right models, define paths to navigate technical or business challenges, develop proof-of-concepts, and make plans for launching solutions at scale. The GenAI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost efficiently. You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. We’re looking for Data Scientists capable of using GenAI and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems. This position requires that the candidate selected be a US Citizen. Key job responsibilities As an Data Scientist, you will * Collaborate with AI/ML scientists and architects to Research, design, develop, and evaluate cutting-edge generative AI algorithms to address real-world challenges * Interact with customers directly to understand the business problem, help and aid them in implementation of generative AI solutions, deliver briefing and deep dive sessions to customers and guide customer on adoption patterns and paths to production * Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder * Provide customer and market feedback to Product and Engineering teams to help define product direction About the team About AWS Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (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 in the cloud. Sales, Marketing and Global Services (SMGS) AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector. The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success. AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services.