Careers

This position requires that the candidate selected be a US Citizen and currently possess and maintain an active Top Secret security clearance. Join a sizeable team of data scientists, research scientists, and machine learning engineers that develop vision language models (VLMs) on overhead imagery for a high-impact government customer. We own the entire machine learning development life cycle, developing models on customer data: - Exploring the data and brainstorming and prioritizing ideas for model development - Implementing new features - Training models in support of experimental or performance goals - T&E-ing, packaging, and delivering models We perform this work on both unclassified and classified networks, with portions of our team working on each network. We seek a new team member to work on the classified networks. You would work collaboratively with teammates to develop and use a python codebase for fine-tuning VLMs. You would have great opportunities to learn from team members and technical leads, while also having opportunities for ownership of important project workflows. You would work with Jupyter Notebooks, the Linux command line, GitLab, and Visual Studio Code. Key job responsibilities With support from technical leads, carry out tasking across the entire machine learning development lifecycle to fine-tune VLMs on overhead imagery: - Run data conversion pipelines to transform customer data into the structure needed by models for training - Perform EDA on the customer data - Train VLMs on overhead imagery - Develop and implement hyper-parameter optimization strategies - Test and Evaluate models and analyze results - Package and deliver models to the customer - Implement new features to the code base - Collaborate with the rest of the team on long term strategy and short-medium term implementation. - Contribute to presentations to the customer regarding the team’s work.

This position requires that the candidate selected be a US Citizen and currently possess and maintain an active Top Secret security clearance. Join a sizeable team of data scientists, research scientists, and machine learning engineers that develop computer vision models on overhead imagery for a high-impact government customer. We own the entire machine learning development life cycle, developing models on customer data: - Exploring the data and brainstorming and prioritizing ideas for model development - Implementing new features in our sizable code base - Training models in support of experimental or performance goals - T&E-ing, packaging, and delivering models We perform this work on both unclassified and classified networks, with portions of our team working on each network. We seek a new team member to work on the classified networks. Three to four days a week, you would travel to the customer site in Northern Virginia to perform tasking as described below. Weekdays when you do not travel to the customer site, you would work from your local Amazon office. You would work collaboratively with teammates to use and contribute to a well-maintained code base that the team has developed over the last several years, almost entirely in python. You would have great opportunities to learn from team members and technical leads, while also having opportunities for ownership of important project workflows. You would work with Jupyter Notebooks, the Linux command line, Apache AirFlow, GitLab, and Visual Studio Code. We are a very collaborative team, and regularly teach and learn from each other, so, if you are familiar with some of these technologies, but unfamiliar with others, we encourage you to apply - especially if you are someone who likes to learn. We are always learning on the job ourselves. Key job responsibilities With support from technical leads, carry out tasking across the entire machine learning development lifecycle to develop computer vision models on overhead imagery: - Run data conversion pipelines to transform customer data into the structure needed by models for training - Perform EDA on the customer data - Train deep neural network models on overhead imagery - Develop and implement hyper-parameter optimization strategies - Test and Evaluate models and analyze results - Package and deliver models to the customer - Incorporate model R&D from low-side researchers - Implement new features to the model development code base - Collaborate with the rest of the team on long term strategy and short-medium term implementation. - Contribute to presentations to the customer regarding the team’s work.

Amazon Prime is looking for an ambitious Economist to help create econometric insights for world-wide Prime. Prime is Amazon's premiere membership program, with over 200M members world-wide. This role is at the center of many major company decisions that impact Amazon's customers. These decisions span a variety of industries, each reflecting the diversity of Prime benefits. These range from fast-free e-commerce shipping, digital content (e.g., exclusive streaming video, music, gaming, photos), reading, healthcare, and grocery offerings. Prime Science creates insights that power these decisions. As an economist in this role, you will create statistical tools that embed causal interpretations. You will utilize massive data, state-of-the-art scientific computing, econometrics (causal, counterfactual/structural, experimentation), and machine-learning, to do so. Some of the science you create will be publishable in internal or external scientific journals and conferences. You will work closely with a team of economists, applied scientists, data professionals (business analysts, business intelligence engineers), product managers, and software/data engineers. You will create insights from descriptive statistics, as well as from novel statistical and econometric models. You will create internal-to-Amazon-facing automated scientific data products to power company decisions. You will write strategic documents explaining how senior company leaders should utilize these insights to create sustainable value for customers. These leaders will often include the senior-most leaders at Amazon. The team is unique in its exposure to company-wide strategies as well as senior leadership. It operates at the research frontier of utilizing data, econometrics, artificial intelligence, and machine-learning to form business strategies. A successful candidate will have demonstrated a capacity for building, estimating, and defending statistical models (e.g., causal, counterfactual, machine-learning) using software such as R, Python, or STATA. They will have a willingness to learn and apply a broad set of statistical and computational techniques to supplement deep training in one area of econometrics. For example, many applications on the team motivate the use of structural econometrics and machine-learning. They rely on building scalable production software, which involves a broad set of world-class software-building skills often learned on-the-job. As a consequence, already-obtained knowledge of SQL, machine learning, and large-scale scientific computing using distributed computing infrastructures such as Spark-Scala or PySpark would be a plus. Additionally, this candidate will show a track-record of delivering projects well and on-time, preferably in collaboration with other team members (e.g. co-authors). Candidates must have very strong writing and emotional intelligence skills (for collaborative teamwork, often with colleagues in different functional roles), a growth mindset, and a capacity for dealing with a high-level of ambiguity. Endowed with these traits and on-the-job-growth, the role will provide the opportunity to have a large strategic, world-wide impact on the customer experiences of Prime members.

This position requires that the candidate selected be a US Citizen and currently possess and maintain an active Top Secret security clearance. Join a sizeable team of data scientists, research scientists, and machine learning engineers that develop vision language models (VLMs) on overhead imagery for a high-impact government customer. We own the entire machine learning development life cycle, developing models on customer data: - Exploring the data and brainstorming and prioritizing ideas for model development - Implementing new features - Training models in support of experimental or performance goals - T&E-ing, packaging, and delivering models We perform this work on both unclassified and classified networks, with portions of our team working on each network. We seek a new team member to work on the classified networks. You would work collaboratively with teammates to develop and use a python codebase for fine-tuning VLMs. You would have great opportunities to learn from team members and technical leads, while also having opportunities for ownership of important project workflows. You would work with Jupyter Notebooks, the Linux command line, GitLab, and Visual Studio Code. Key job responsibilities With support from technical leads, carry out tasking across the entire machine learning development lifecycle to fine-tune VLMs on overhead imagery: - Run data conversion pipelines to transform customer data into the structure needed by models for training - Perform EDA on the customer data - Train VLMs on overhead imagery - Develop and implement hyper-parameter optimization strategies - Test and Evaluate models and analyze results - Package and deliver models to the customer - Implement new features to the code base - Collaborate with the rest of the team on long term strategy and short-medium term implementation. - Contribute to presentations to the customer regarding the team’s work.

This position requires that the candidate selected be a US Citizen and currently possess and maintain an active Top Secret security clearance. Join a sizeable team of data scientists, research scientists, and machine learning engineers that develop computer vision models on overhead imagery for a high-impact government customer. We own the entire machine learning development life cycle, developing models on customer data: Exploring the data and brainstorming and prioritizing ideas for model development Implementing new features in our sizable code base Training models in support of experimental or performance goals T&E-ing, packaging, and delivering models We perform this work on both unclassified and classified networks, with portions of our team working on each network. We seek a new team member to work primarily on the unclassified networks. You would work collaboratively with teammates to use and contribute to a well-maintained code base that the team has developed over the last several years, almost entirely in python. You would have great opportunities to learn from team members and technical leads, while also having opportunities for ownership of important project workflows. You would work with Jupyter Notebooks, the Linux command line, AWS Services, GitLab, and Visual Studio Code. We are a very collaborative team, and regularly teach and learn from each other, so, if you are familiar with some of these technologies, but unfamiliar with others, we encourage you to apply - especially if you are someone who likes to learn. We are always learning on the job ourselves. Key job responsibilities With support from technical leads, carry out tasking across the entire machine learning development lifecycle to develop computer vision models on overhead imagery: Run data conversion pipelines to transform customer data into the structure needed by models for training Perform EDA on the customer data Train deep neural network models on overhead imagery Develop and implement hyper-parameter optimization strategies Test and Evaluate models and analyze results Package and deliver models to the customer Implement new features to the model development code base Collaborate with the rest of the team on long term strategy and short-medium term implementation. Contribute to presentations to the customer regarding the team’s work.

Amazon Industrial Robotics (AIR) is seeking exceptional talent to help develop the next generation of advanced robotics systems that will transform automation at Amazon's scale. We're building revolutionary robotic systems that combine cutting-edge AI, sophisticated control systems, and advanced mechanical design to create adaptable automation solutions capable of working safely alongside humans in dynamic environments. This is a unique opportunity to shape the future of robotics and automation at an unprecedented scale, working with world-class teams pushing the boundaries of what's possible in robotic dexterous manipulation, locomotion, and human-robot interaction. This role presents an opportunity to shape the future of robotics through innovative applications of the latest software and AI tools for robots. We are seeking an expert to lead the development of our SLAM and Spatial AI module. In this role, you will create methods that will enable our robot to perceive the environment and navigate with unrivaled vision and fidelity. The system will combine an array of diverse sensors with simultaneous localization and mapping software that continuously updates the map in real-time automatically. It will have the capability to ‘see’ and identify different objects, people, vehicles, and places as it moves and react to moving people and vehicles in an intelligent way. The system combines a mix of high-performance sensors with simultaneous localization and mapping software that builds and continuously updates maps in real-time, completely automatically. It has the capability to ‘see’ and identify different objects, people, vehicles, and places as it moves and react to moving people and vehicles in an intelligent way. Key job responsibilities - Analyze, design, develop, and test existing and new perception capabilities using cameras and LIDAR sensor inputs for obstacle detection and semantic understanding. - Research, design, implement and evaluate scientific approaches to a variety of autonomy challenges.. - Create experiments and prototype implementations of new perception algorithms. - Deliver high quality production level code (C++ or Python) and support systems in production. - Collaborate with other functional teams in a robotics organization. - Collaborate closely with hardware engineering team members on developing systems from prototyping to production level. - Represent Amazon in academia community through publications and scientific presentations. - Work with stakeholders across hardware, science, and operations teams to iterate on systems design and implementation.

Why this job is awesome? - This is SUPER high-visibility work: Our mission is to provide consistent, accurate, and relevant delivery information to every single page on every Amazon-owned site. - MILLIONS of customers will be impacted by your contributions: The changes we make directly impact the customer experience on every Amazon site. This is a great position for someone who likes to leverage Machine learning technologies to solve the real customer problems, and also wants to see and measure their direct impact on customers. - We are a cross-functional team that owns the ENTIRE delivery experience for customers: From the business requirements to the technical systems that allow us to directly affect the on-site experience from a central service, business and technical team members are integrated so everyone is involved through the entire development process. - Do you want to join an innovative team of scientists and engineers who use optimization, machine learning and Gen-AI techniques to deliver the best delivery experience on every Amazon-owned site? - Are you excited by the prospect of analyzing and modeling terabytes of data on the cloud and create state-of-art algorithms to solve real world problems? - Do you like to own end-to-end business problems/metrics and directly impact the same-day delivery service of Amazon? - Do you like to innovate and simplify? If yes, then you may be a great fit to join the Delivery Experience Machine Learning team! Key job responsibilities · Research and implement Optimization, ML and Gen-AI techniques to create scalable and effective models in Delivery Experience (DEX) systems · Design and develop optimization models and reinforcement learning models to improve quality of same-day selections · Apply LLM technology to empower CX features · Establishing scalable, efficient, automated processes for large scale data analysis and causal inference

The Amazon Center for Quantum Computing (CQC) is a multi-disciplinary team of scientists, engineers, and technicians, on a mission to develop a fault-tolerant quantum computer. We are looking for a Last Mile Integration Engineer to ensure the successful deployment and integration of instruments and computing infrastructure in our quantum computing labs. As a part of the Signals team, you will serve as the critical link between hardware/software development and operational readiness, ensuring that our scientists have reliable, well-configured systems to conduct experiments. The ideal candidate combines hands-on hardware skills with software proficiency and IT/networking knowledge to deploy, configure, troubleshoot, and maintain complex laboratory systems. Key job responsibilities Own end-to-end integration of RF test systems including spectrum analyzers, signal generators, network analyzers, oscilloscopes, DMMs, and power meters Design, develop, and maintain automation scripts and frameworks leveraging industry-standard protocols (SCPI, VISA, GPIB, LXI, USB-TMC) Drive root cause analysis for system-level integration failures spanning hardware and software; implement corrective actions and document findings for future reference Partner with hardware, software, and operations engineering teams to identify and resolve blocking issues in test infrastructure Define and implement lab infrastructure management processes including inventory tracking, equipment lifecycle management, and spare parts optimization Lead calibration activities, measurement validation, and continuous improvement of test automation capabilities Establish remote debugging capabilities and participate in on-call rotation to ensure operational readiness Champion lab safety standards and ensure compliance with ESD, RF exposure, and high-voltage protocols A day in the life You will collaborate daily with cross-functional engineering teams—including hardware, software, and operations—to drive hands-on integration and troubleshooting in a fast-paced lab environment. This role requires a bias for action, the ability to operate independently under tight deadlines, and a proven track record of delivering results when the pressure is highest. The Signals develops and deploys hardware used in the control and readout of Amazon super-conducting quantum processors. We are a team with diverse talent set, spanning embedded software to cryogenic microwave design and device bring-up. 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 AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do. 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. Internal job description

Leo is Amazon’s low Earth orbit satellite broadband network. Its mission is to deliver fast, reliable internet to customers and communities around the world, and we’ve designed the system with the capacity, flexibility, and performance to serve a wide range of customers, from individual households to schools, hospitals, businesses, government agencies, and other organizations operating in locations without reliable connectivity. The Sr. Applied Scientist Pricing Optimization, Leo Global Pricing Strategy will have an outsized impact on the profitability of Amazon Leo directly through building the initial foundational models to enable the business to optimize our pricing and product feature strategies. You will be building a true "0 to 1" function, powering the science behind pricing decisions and driving science automation at a global scale. 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. A day in the life You will design, develop, and deploy advanced machine‑learning models to predict customer‑level behavior (revenue, churn, usage, migration, product choice) and response to pricing changes. You will build robust models that capture the complexities of multi‑product bundling interactions in a subscription business model and regional nuances in supply/demand and consumer choice alternative choices. You will implement scalable inference systems, will monitor model performance, and will automate retraining. Collaboration with cross‑functional teams will be critical to ensure that technical solutions will align with business objectives and actionable strategies. Establishing mechanisms to stay up to date on latest scientific advancements in machine learning, neural networks, natural language processing, probabilistic forecasting, and multi-objective optimization techniques will be critical.

The People eXperience and Technology Central Science (PXTCS) team uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, wellbeing, and the value of work to Amazonians. PXTCS is an interdisciplinary team that combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal. PXTCS is looking for an economist who can apply economic methods to address business problems. The ideal candidate will work with engineers and computer scientists to estimate models and algorithms on large scale data, design pilots and measure impact, and transform successful prototypes into improved policies and programs at scale. PXTCS is looking for creative thinkers who can 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 will work in a team setting with individuals from diverse disciplines and backgrounds. They will work with teammates to develop scientific models and conduct the 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. A day in the life The Economist will work with teammates to apply economic methods to business problems. This might include identifying the appropriate research questions, writing code to implement a DID analysis or estimate a structural model, or writing and presenting a document with findings to business leaders. Our economists also collaborate with partner teams 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 PXTCS is a multidisciplinary science team that develops innovative solutions to make Amazon Earth's Best Employer