Research Science

Amazon is looking for talented Postdoctoral Scientists to join our Forward Looking Initiatives & Technology Enablers (FLITE) Team for a one-year, full-time research position. The Forward Looking Initiatives & Technology Enablers (FLITE) Team. FLITE’s charter is to enable Amazon Robotics Manipulation Organization to innovate on advanced technology development. The research work for this position will explore generalization of imitation learning based policies on novel hardware platforms. This will include exploring alternative representations and foundation models. The candidate will prototype algorithms in simulation and then deploy promising solutions to real and novel hardware.Key job responsibilities• Work closely with a senior science advisor, collaborate with other scientists and engineers, and be part of Amazon’s vibrant and diverse global science community.• Publish your innovation in top-tier academic venues and hone your presentation skills.• Be inspired by challenges and opportunities to invent cutting-edge techniques in your area(s) of expertise. We are open to hiring candidates to work out of one of the following locations:Cambridge, MA, USA | North Reading, MA, USABASIC QUALIFICATIONS• PhD in a relevant field, received within 2 years of starting the program• Proven publication record in Manipulation and Gasp Learning• Publications in related topics in Machine Learning, Robotics, Computer Vision, AI, Computer Science, Econ, Reinforcement Learning or other related technical fields• Experience in data science and quantitative research• Proficiency in technologies relevant to the subfield ...

Are you inspired by invention? Is problem solving through teamwork in your DNA? Do you like the idea of seeing how your work impacts the bigger picture? Answer yes to any of these and you’ll fit right in here at Amazon Robotics. We are a smart team of doers that work passionately to apply cutting edge advances in robotics and software to solve real-world challenges that will transform our customers’ experiences in ways we can’t even imagine yet. We invent new improvements every day. We are Amazon Robotics and we will give you the tools and support you need to invent with us in ways that are rewarding, fulfilling and fun. The Research Science team at Amazon Robotics is seeking interns with a passion for robotic research to work on cutting edge algorithms for robotics. Our team works on challenging and high-impact projects, including allocating resources to complete a million orders a day, coordinating the motion of thousands of robots, autonomous navigation in warehouses, and learning how to grasp all the products Amazon sells. We are seeking internship candidates with backgrounds in computer vision, machine learning, resource allocation, discrete optimization, search, planning/scheduling, and reinforcement learning. As an intern you will develop a new algorithm to solve one of the challenging computer vision and manipulation problems in Amazon's robotic warehouses. Your project will fit your academic research experience and interests. You will code and test out your solutions in increasingly realistic scenarios and iterate on the idea with your mentor to find the best solution to the problem. BASIC QUALIFICATIONS- Currently enrolled in a PhD program in Computer Science, Engineering, Machine Learning, Operations Research or similar with a graduation date after December 2025- Must be available and eligible for a full-time (40h/week) internship between May/June and August/September 2025- At least two years of relevant academic research in state-of-the-art approaches for at least one of computer vision, resource allocation, optimization, planning, machine learning, or reinforcement learning- Fluency in at least one statistical software package such as R, Stata, or Matlab- Experience with programming languages such as Java, C++, Python ...

As a Senior Applied Scientist specializing in Large Language Models (LLMs) and Natural Language Processing (NLP) in the Product Intelligence team, you will lead the development of machine learning solutions. Your work will leverage the latest LLMs and multimodal models to enhance product graphs, measure entity similarity, perform entity linking, and attribute normalization, and apply advanced reasoning methods for a deeper understanding of products. You will also lead research projects to tackle unsolved problems, mentor interns, and author academic papers to summarize your findings for external publication. This high-impact role is critical to our core business, influencing the reliability of information for billions of products on Amazon's platform, and impacting the shopping journey for hundreds of millions of customers. The systems you build will be used to monitor Amazon's entire product selection to ensure their quality, the availability of accurate price distributions, and more.We seek an experienced scientist with deep knowledge of LLMs and NLP, and a good understanding of traditional machine learning and quantitative methods. The role will also require cross-functional collaboration skills, and staying up to date with the latest advancements in Generative AI.Key job responsibilities- Implement and deploy systems that leverage LLMs and other techniques to address some of hardest problems in the pricing space.- Set scientific standards and see the big picture to influence Amazon's long-term vision for retail pricing science.- Work cross-functionally with various teams to align machine learning initiatives with business goals and execute them successfully.- Lead research projects and participate in the publication of external academic papers at top conferences and journals.About the teamRetail pricing science is a centralized diverse team of STEM scientists that develop statistical, ML, RL, optimization and economic models that drive pricing for products sold by Amazon worldwide, as well as monitoring of prices and experimentations in pricing. The team has a dual focus on competitiveness and long term financial optimality.BASIC QUALIFICATIONS- PhD, or Master's degree and 10+ years of applied research experience- 4+ years of applied research experience- 4+ years of building machine learning models for business application experience- Experience programming in Java, C++, Python or related language- Experience with neural deep learning methods and machine learning ...

Amazon Music is an immersive audio entertainment service that deepens connections between fans, artists, and creators. From personalized music playlists to exclusive podcasts, concert livestreams to artist merch, Amazon Music is innovating at some of the most exciting intersections of music and culture. We offer experiences that serve all listeners with our different tiers of service: Prime members get access to all the music in shuffle mode, and top ad-free podcasts, included with their membership; customers can upgrade to Amazon Music Unlimited for unlimited, on-demand access to 100 million songs, including millions in HD, Ultra HD, and spatial audio; and anyone can listen for free by downloading the Amazon Music app or via Alexa-enabled devices. Join us for the opportunity to influence how Amazon Music engages fans, artists, and creators on a global scale. Learn more at https://www.amazon.com/music.We are seeking a highly skilled and analytical Resesarch Scientist. You will play an integral part in the measurement and optimization of Amazon Music marketing activities. You will have the opportunity to work with a rich marketing dataset together with the marketing managers. This role will focus on developing and implementing causal models and randomized controlled trials to assess marketing effectiveness and inform strategic decision-making. This role is suitable for candidates with strong background in causal inference, statistical analysis, and data-driven problem-solving, with the ability to translate complex data into actionable insights. As a key member of our team, you will work closely with cross-functional partners to optimize marketing strategies and drive business growth.Key job responsibilitiesDevelop Causal ModelsDesign, build, and validate causal models to evaluate the impact of marketing campaigns and initiatives. Leverage advanced statistical methods to identify and quantify causal relationships.Conduct Randomized Controlled TrialsDesign and implement randomized controlled trials (RCTs) to rigorously test the effectiveness of marketing strategies. Ensure robust experimental design and proper execution to derive credible insights.Statistical Analysis and InferencePerform complex statistical analyses to interpret data from experiments and observational studies. Use statistical software and programming languages to analyze large datasets and extract meaningful patterns.Data-Driven Decision MakingCollaborate with marketing teams to provide data-driven recommendations that enhance campaign performance and ROI. Present findings and insights to stakeholders in a clear and actionable manner.Collaborative Problem SolvingWork closely with cross-functional teams, including marketing, product, and engineering, to identify key business questions and develop analytical solutions. Foster a culture of data-informed decision-making across the organization.Stay Current with Industry TrendsKeep abreast of the latest developments in data science, causal inference, and marketing analytics. Apply new methodologies and technologies to improve the accuracy and efficiency of marketing measurement.Documentation and ReportingMaintain comprehensive documentation of models, experiments, and analytical processes. Prepare reports and presentations that effectively communicate complex analyses to non-technical audiences.BASIC QUALIFICATIONS- PhD in a quantitative field, or MS degree and 1+ years of quantitative field research experience- Experience investigating the feasibility of applying scientific principles and concepts to business problems and products- Experience with data analysis package (R, SAS, Matlab, etc.)- Experience using SQL databases to manage and analyze large data sets ...

The Fulfillment by Amazon (FBA) and Supply Chain by Amazon (SCA) enable third-party sellers to use Amazon’s world-class science and logistics infrastructure to supply and fulfill customers world-wide with unprecedented fast delivery promise to customer. In doing so, sellers spend more time building great products, delight customers and grow their business. The FBA team is looking for a passionate, curious, and creative Principal Research Scientist with expertise in operations research, machine learning or statistics, along with a proven record of solving business problems through scalable modeling and analytical skills. As a lead research scientist in the team, you will be responsible for designing and implementing cutting edge optimization and ML models, building automated inventory, logistics and revenue management systems while collaborating with business and software teams to solve key challenges facing the worldwide FBA business. Such challenges include 1) designing end-to-end supply and demand management systems, ranging from capacity, inventory, and workforce management systems, 2) developing and improving optimization and ML models to help FBA sellers grow their business, 3) ensuring that worldwide Amazon customers have access to the largest selection of products through FBA sellers, and 4) driving out costs across end-to-end FBA supply chain. Unlike many companies who buy existing off-the-shelf planning systems, we design and build systems to suit Amazon’s particular needs. Our team members are 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, research scientists, statisticians, economists and software developers in the business. We value individuals who exhibit deep technical proficiency, a desire for learning new areas, and a track record of delivering tangible results while fostering personal growth, team development, and career advancement.A day in the lifeIn this pivotal role, you will be a technical leader in operations research or machine learning, with significant scope, impact, and visibility. Your solutions have the potential to drive billions of dollars in impact for Amazon's third-party seller business. As a senior scientist on the team, you will engage in every facet of the process—from idea generation, business analysis and scientific research to development and deployment of advanced models—granting you a profound sense of ownership. From day one, you will collaborate with experienced scientists, engineers, and product managers who are passionate about their work. Moreover, you will collaborate with Amazon's broader decision and research science community, enriching your perspective and mentoring fellow engineers and scientists. The successful candidate will have the strong expertise in applying operations research methodologies to address a wide variety of supply chain problems with millions of unique products involving hundreds of thousands of Selling Partners and tens of millions of customers worldwide. You will strive for simplicity, demonstrate judgment backed by mathematical rigor, as you continually seek opportunities to innovate, build, and deliver. Entrepreneurial spirit, adaptability to diverse roles, and agility in a fast-paced, high-energy, highly collaborative environment are essential. About the teamSellers play a vital role in Amazon’s ecosystem, integral to our mission of offering the Earth’s largest selection and lowest prices. FBA is a service that enables third-party sellers to outsource order fulfillment to Amazon, and leverage Amazon’s world-class facilities to provide customers Prime delivery promise. By partnering with Amazon, sellers benefit from powerful, cost-effective solutions that leverage our scale and technology, gain access to Prime members worldwide, increase their sales, and have more time to continue inventing amazing products for customers. With commitment to taking on even more of the supply chain and operational complexities on behalf of our selling partners, Amazon introduced Supply Chain by Amazon (SCA), an end-to-end, fully automated suite of supply chain services. This comprehensive solution empowers sellers to quickly and reliably transport products from manufacturing sites to customers worldwide. Amazon Warehousing and Distribution is a pivotal service in SCA, that provides best-in-class bulk storage and distribution services to sellers, ensuring they remain well-stocked across all their sale and fulfillment channels while reducing the total supply chain costs. The FBA team is the core group in charge of fulfillment, inventory management, pricing, and a diverse range of operational recommendation services for sellers, as well as building the internal resource management systems. We work to learn seller behavior, understand seller experience, build automated assistants to sellers, recommend right actions to sellers, design seller policies and incentives, and develop science products and services that empower third-party sellers to grow their businesses. To do so, we build and innovate science solutions at the intersection of machine learning, statistics, economics, operations research, and data analytics. We work full-stack, from foundational backend systems to future-forward user interfaces. Our culture is centered on rapid prototyping, rigorous experimentation, and data-driven decision-making.BASIC QUALIFICATIONS- Ph.D. in Operations Research, Machine Learning, Statistics, Computer Science, Applied Mathematics, Operations Management, Industrial Engineering, Economics or a related field.- 7+ years of experience in solving complex problems in the area of operations research, statistics or machine learning, as well as in developing strategies for large-scale supply chain, transportation and logistic networks.- Ability to perform quantitative, economic, and numerical analyses of large-scale systems under uncertainty using statistical and optimization tools such as Python, R and XPRESS to determine solution strategies for complex decision-making problems.- Fluency in using mathematical optimization or machine learning, including algorithm design, continuous and discrete optimization, stochastic analysis, supervised and unsupervised machine learning methods, and deep learning, to develop solution methods to be used by in-house decision support tools and software.- Proficiency working with Python, SQL and/or C/C++.- Excellent written and verbal communication skills while addressing both technical and business people, ability to speak at a level appropriate for the audience, and skills to present business cases, and document models, analyses, and results to influence important decisions. ...

Do you want to be part of the team developing the future technology that impacts the customer experience of ground-breaking products? Then come join us and make history.We are looking for a passionate, talented, and inventive Applied Scientist with a background in AI, Gen AI, Machine Learning, NLP, to help build LLM solutions for Amazon core shopping.Our team works on a variety of projects, including state of the art generative AI, LLM finetuning, alignment, prompt engineering, benchmarking solutions.Key job responsibilitiesAs an Applied Scientist will be expected to work on state of the art technologies which will result in papers publications, however you will not be only theorizing about the algorithms, but you will also have the opportunity to implement them and see how they behave in the field.This is an incredible opportunity to validate your research on one of the most exciting Amazon AI products, where assumptions can be tested against real business scenarios and supported by an abundance of data.BASIC QUALIFICATIONS- Experience programming in Java, C++, Python or related language- Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse- Advanced degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field ...

mmPROS Surface Research Science seeks an exceptional Applied Scientist with expertise in forecasting and risk modeling to optimize Amazon's middle mile transportation network, the backbone of its logistics operations. Amazon's middle mile transportation network utilizes a fleet of semi-trucks, trains, and air planes to transport millions of packages per day as well as other freight between warehouses, vendor facilities, and customers, on time and at low cost. The mmPROS Surface Research Science team delivers innovation, models, algorithms, and other scientific solutions to efficiently plan and operate the middle mile surface (truck and rail) transportation network. The team focuses on large-scale problems in vehicle route planning, capacity procurement, network design, forecasting, and equipment re-balancing. Your role will be to build innovative forecasting, risk quantification, and other machine learning models to decide the optimal long-term and short-term strategy for truck capacity procurement and other planning problems.Your models will impact business decisions worth billions of dollars and improve the delivery experience for millions of customers. You will operate as part of a team of innovative, experienced scientists working on machine learning and optimization problems, and you will work in close collaboration with partners across product, engineering, business intelligence, and operations. Key job responsibilities- Design, develop, and implement forecasting models, risk models, and other machine learning models to inform our hardest planning decisions.- Implement machine learning and risk models in Amazon's production software.- Lead and partner with product, engineering, and operations teams to drive modeling and technical design for complex business problems.- Lead complex modeling and data analyses to aid management in making key business decisions and set new policies.- Write documentation for scientific and business audiences.About the teamThis role is part of mmPROS Surface Research Science. Our mission is to build the most efficient and optimal transportation network on the planet, using our science and technology as our biggest advantage. We aim to leverage cutting edge technologies in optimization, operations research, and machine learning to grow our businesses and solve Amazon's unique logistical challenges.Scientists in the team work in close collaboration with each other and with partners across product, software engineering, business intelligence, and operations. They regularly interact with software engineering teams and business leadership.BASIC QUALIFICATIONS- PhD, or Master's degree and 4+ years of science, technology, engineering or related field experience- 1+ years of programming in Java, C++, Python or related language experience- Experience building machine learning models or developing algorithms for business application ...

The North America Capacity Planning team in Amazon Stores' Supply Chain organization is charged with planning, managing, and optimizing the use of inbound, storage, and fulfillment capacity in North America. Optimal planning and usage of this capacity is critical in enabling us to deliver several billion items annually at continually lower costs and higher speeds. The decision space extends from tactical short-term actions (what capacity constraints do we face next week and how do we alleviate them?) to large-scale long-term strategy (what kind of fulfillment capacity should we invest in, where, over the next three years?). The team works in close partnership with several other business and tech teams to develop capacity plans, and ensure the delivery and optimal use of fulfillment capacity. As a Principal Research Scientist in this team, you will interact with subject matter experts within and outside the team, as well as scientists in a range of partner organizations, to develop scientific models for capacity planning and optimization. You will leverage these models to influence senior leadership to make high-impact decisions that are critical to building Amazon's future supply chain. You will also be an active participant in the overall Amazon scientific community, generating intellectual capital, participating in reviews and conferences, publishing in internal and external venues, and incorporating scientific rigor in the team's practices. Key job responsibilities- Develop scientific models for large-scale fulfillment capacity planning under uncertainty- Partner with stakeholder science teams for development and use of their scientific models for various aspects of capacity planning such as demand estimation, inventory flows, and multi-echelon supply chain management- Develop strategic plans for long-term capacity investments, in close collaboration with subject matter experts within and outside the team- Influence senior leadership on large-scale one-way capital and technological investments for designing our future fulfillment network- Partner with scientists across Amazon in developing scientific models that jointly optimize the Amazon supply chain BASIC QUALIFICATIONS- 10+ years of tech industry or equivalent experience- Experience with complex supply chains (>100 facilities, >1000 routes)- PhD in a quantitative discipline such as operations research, industrial engineering, computer science, economics, or an equivalent quantitative field. ...

The Jr. Applied Scientist role is a unique employment opportunity for students seeking to gain on-the-job applied science and machine learning experience and receive excellent mentoring while completing their education. Jr. Applied Scientists are immersed in an Amazon team and work on exciting, meaningful projects that impact real Amazon customers. Paired 1:1 with a Amazon Applied Science Mentor, Jr. Applied Scientists receive guidance and support in all aspects of their role: skill development, career advisement, project collaboration, and more! Upon successful completion of your degree and success in the Jr. Applied Scientist role, the opportunity for full-time employment may be available at an Amazon corporate site. The Jr. Applied Scientist role is part of the Jr. Developer Program, a unique internship program in several respects:• We offer work year-round, part-time (16 hrs/week) while in school and full-time (40hrs/week) during summer. Working schedules are flexible and can be re-arranged each quarter to accommodate class schedules. • We offer excellent mentoring. Our full-time applied scientists, data scientists, business intelligence engineers, and software development engineers are willing and able to mentor exceptional student applied scientists, data scientists, SDEs, and BIEs. • Jr. Applied Scientists are given responsibilities and roles that prepare them to enter the workforce after graduation with “real world” applied science and machine learning experience. Jrs. who participate in the Jr. Developer Program routinely acknowledge the valuable learning experience created by the uniform excellence of their teams, mentoring offered by experienced Amazonians, and the challenge of being a principal contributor to science and software products. Key job responsibilities• Amazon applied scientists are specialists with the knowledge to help drive the scientific vision for our products. They are aware of the state-of-the-art in their respective field of expertise and are constantly focused on advancing that state-of-the-art for improving Amazon’s products and services.• As a Jr. Applied Scientist at Amazon, you will connect with world leaders in your field working on similar problems. You will be working with distributed systems of data and providing technical partnership to the product managers, teams, and organizations building machine learning solutions. You will be tackling Machine Learning challenges in Supervised, Unsupervised, and Semi-supervised Learning; utilizing modern methods such as deep learning and classical methods from statistical learning theory, detection, estimation.• This individual will analyze large amounts of data, discover and solve real world problems and build metrics and business cases around key performance of this program. • The ideal candidate will use a customer backwards approach in deriving insights and identifying actions we can take to improve the customer experience and conversion for the program.BASIC QUALIFICATIONS- Currently enrolled in an accredited college or university Master's degree program.- Majoring in Computer Science, Statistics or a related STEM discipline.- Graduating in June 2027 and beyond. - Ability to work year-round: part-time during the school year and full-time during the summer.- This role is not offered as remote or hybrid and working hours must be conducted in our corporate office in San Diego.- Living within commutable distance to San Diego, CA and able to work in-person. ...

Here at Amazon, we embrace our differences. We are committed to furthering our culture of diversity and inclusion of our teams within the organization.How do you get items to customers quickly, cost-effectively, and—most importantly—safely, in less than an hour? And how do you do it in a way that can scale? Our teams of hundreds of scientists, engineers, aerospace professionals, and futurists have been working hard to do just that! We are delivering to customers, and are excited for what’s to come. Check out more information about Prime Air on the About Amazon blog (https://www.aboutamazon.com/news/transportation/amazon-prime-air-delivery-drone-reveal-photos).If you are seeking an iterative environment where you can drive innovation, apply state-of-the-art technologies to solve real world delivery challenges, and provide benefits to customers, Prime Air is the place for you.Come work on the Amazon Prime Air Team!Our Prime Air Drone Flight Sciences High Fidelity Methods (HFM) team is looking for an outstanding member to develop and verify our Aerodynamic Database and associated aerodynamics models used for engineering analyses and vehicle simulations. These models are the backbone of every flight simulation performed within Prime Air and are a critical element in the aircraft design, verification, and certification process.These models are used to predict many attributes of the vehicle performance including range, maneuverability, tracking error, and aircraft stability. They are a key input to design decisions, vehicle component sizing and flight software algorithm development. The accuracy and reliability of these flight model are critical to the success of Prime Air.Key job responsibilitiesThe person in this role is responsible for owning the development, deployment, verification, and maintenance of models from end-to-end. This includes the initial gathering of the downstream customer needs, identifying the most suitable modelling approach, coordinating the generation of input data, training models, developing and maintaining software interfaces, and verifying the model accuracy.This person will also be responsible for determining the most suitable modeling approach for a given physical phenomena. They need to possess knowledge of various machine learning techniques, and their respective advantages and limitations. They will need to have a detailed understanding of the types of physics to be modelled including vehicle aerodynamics, multibody dynamics, and atmosphere physics. They will be responsible for designing experiments for generating data used to train and verify surrogate models. They need to have a basic understanding of the methods used to generate high-fidelity aerodynamics predictions including CFD, wind tunnel testing, and flight testing. They will be responsible for validating the models by leveraging uncertainty quantification, system identification, and statistical analyses.BASIC QUALIFICATIONS- Bachelors Degree in aerospace engineering, mechanical engineering, physics and 5+ years experience or equivalent- Experience with flight vehicle design, simulation, development, and verification & validation (V&V)- Proficient with at least one modern programming language (e.g. C++, Python, Java, VBA) ...

Join our Amazon Private Brands Selection Guidance organization in building science and tech solutions at scale to delight our customers with products across our leading private brands such as Amazon Basics, Amazon Essentials, and by Amazon.The Selection Guidance team applies Generative AI, Machine Learning, Statistics, and Economics solutions to drive our private brands product assortment, strategic business decisions, and product inputs such as title, price, merchandising and ordering. We are an interdisciplinary team of Scientists, Economists, Engineers, and Product Managers incubating and building day one solutions using cutting-edge technology, to solve some of the toughest business problems at Amazon.As a Principal Applied Scientist you will invent novel solutions and prototypes, and directly contribute to bringing your ideas to life through production implementation. Current research areas include entity resolution, generative AI, large language models, and product substitutes. You will review and guide scientists across the team on their designs and implementations, and raise the team bar for science research and prototypes.This is a unique, high visibility opportunity for someone who wants to develop cutting edge science solutions and have direct business and customer impact. Key job responsibilities- Partner with business stakeholders to deeply understand APB business problems and frame ambiguous business problems as science problems and solutions.- Invent novel science solutions and develop prototypes to solve business problems.- Review and guide science solutions across the team.- Publish and socialize your and the team's research across Amazon and external avenues as appropriate- Leverage industry best practices to establish repeatable applied science practices, principles & processes.BASIC QUALIFICATIONS• Ph.D. degree in Statistics, Computer Science, Applied Math, Machine Learning, or a related field• 7+ years of hands-on experience in solving difficult machine learning problems • Experience in patents or publications at top-tier peer-reviewed conferences or journals• Expert at more than one major programming languages (C++, Java, or similar) and at least one scripting language (Perl, Python, or similar)• Demonstrated ability to serve as a technical lead • Excellent writing skills for presenting business cases and scientific models with rigorous analyses that support results/conclusions to influence important decisions.• Strong fundamentals in problem solving, algorithm design and complexity analysis• Proven track in leading, mentoring, and growing teams of scientists ...

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.The AWS Center for Quantum Computing is a multi-disciplinary team of scientists, engineers, and technicians, all working to innovate in quantum computing for the benefit of our customers.We are looking to hire a Senior Research Scientist to develop and test novel calibration and optimization tools for the operation of large scale quantum processors. You will be a technical leader on a team of engineers and scientists at the frontier of quantum processor control and error correction. You are expected to develop & 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 lifeDiverse ExperiencesAWS 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 CultureHere 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 GrowthWe’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 BalanceWe 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. BASIC QUALIFICATIONS- PhD in physics, applied physics, electrical engineering, or an equivalent degree in a similar field- 5+ years of post-PhD or industry experience as an experimentalist in quantum computing- In-the-lab experience calibrating multi-qubit systems- Expertise in common qubit benchmarking and tomographic protocols (e.g. randomized benchmarking)- Proficient in a scientific programming environment- Experience successfully delivering on projects as part of a cross-team collaboration ...

Amazon’s global talent management and compensation (GTMC) organization is looking for a Senior Applied Scientist to join our interdisciplinary science team. The role will lead our strategic science investments to develop and refine Generative AI solutions in our experiences that help more than 1.5 million employees build rewarding careers and shape how we manage Amazon's talent.GTMC is responsible for managing all aspects of Amazon employees' careers, from onboarding to exit. We build intelligent products that are used by employees, their managers and senior leadership to grow, develop and reward Amazon’s talent. The domains we cover include career development, talent evaluation, employee-role matching, promotions, organizational design and succession planning, and new areas that address the evolving needs of our diverse employee base.We are looking for an experienced applied scientist who has experience building, applying and customizing GenAI solutions to solve customer problems. As a senior applied scientist on the team, you will play a critical role in driving the development of GenAI technologies that handle Amazon-scale use cases and have a significant impact on our employees' lives. You will have the opportunity to lead exciting problems, publish and patent your work in one of the most high impact, innovative and unconventional applications of science in the People Experience and Technology space.If this kind of work excites you, reach out to us to find out more!Key job responsibilities- Provide scientific thought leadership in GenAI solution development for our science and engineering teams- Prototype and iterate on GenAI solutions for capabilities across writing feedback, summarization, information retrieval, content generation and orchestration.- Participate in scoping feature and business planning roadmap of GTMC’s science investments- Design and execute science-based product ideas and features, project plans and communicate with stakeholders- Partner with engineers to productionize GenAI and other science models at the scale of Amazon- Mentor and guide junior scientists and engineers, and contribute to the overall growth and development of the teamAbout the teamGTMC's science team is an experienced central interdisciplinary organization of scientists spanning machine learning, economics and research that builds science models for Amazon's worldwide employee-facing talent management products, designs and supports experiments for product features, and measures impact of product and program initiatives across the broader organization. Examples of our work include GenAI-powered summarization and writing assistants, content and people recommendation systems, scalable experimentation products and measuring organizational north star metrics.BASIC QUALIFICATIONS- 3+ years of building machine learning models for business application experience- PhD, or Master's degree and 6+ years of applied research experience- Experience with neural deep learning methods and machine learning- Experience programming in Java, C++, Python or related language- Experience with developing Generative AI solutions for business applications ...

Are you excited about developing generative AI and foundation models to revolutionize automation, text generation, and machine learning at scale? Are you looking for opportunities to build and deploy them on real problems at truly vast scale? At Amazon BuilderWorks we are on a mission to build high-performance autonomous systems that perceive and act to further improve our world-class builder experience - at Amazon scale.This role is for the Data Reserach Org for Insights Development (DROID) Science team which has deep expertise developing cutting edge AI solutions at scale and successfully applying them to business problems in the Stores, Devices, and Other (SDO) organization. These solutions typically utilize machine learning and GenAI techniques, applied to text, sequences of events, wikis, or customer input from existing or new tooling. The team is comprised of scientists, who develop machine learning and deep learning solutions, analytics, who evaluate the expected business impact for a project and the performance of these solutions, and software engineers, who provide necessary support such as annotation pipelines and machine learning library development.We are looking for an Applied Scientist with expertise in GenAI. You will work alongside other scientists, engineers, product managers and various stakeholders to deploy models at scale across a diverse set of initiatives. If you are a self-motivated individual with a zeal for customer obsession and ownership, and are passionate about applying science for real world problems - this is the team for you.Key job responsibilities- You will be part of a team of scientists and engineers and will work on scaling systems to production along side partner teams.- You will learn how to build robust solutions that operate at Amazon scale, and work with senior technical leaders to grow your skills.- You will face a high level of research ambiguity and problems that require creative, ambitious, and inventive solutions.- You will design and implement scalable solutions and solve complex problems- You will mentor and coach junior software developers- You should be a great communicator and should be motivated to achieve results in a fast-paced, and at times ambiguous, environment- You should be a self-starter with a bias towards independent problem solving.About the teamBuilderWorks tools, libraries, and services empower Amazon builders to deliver solutions for a diversity of internal and external customer use-cases spanning the Stores business as our primary customer with additional support for Devices and Other (SDO) business units across Amazon. The DROID team sits within BuilderWorks and seeks to be the primary source for standardized, actionable metrics and science-driven insights within BuilderWorks. We achieve this through user-focused tools that provide comprehensive access to current and future metrics, solutions that provide measurable impact to cost and engagement through the use of scientific methods, user-accessible data repositories for individual analyses and deep divesDROID Science mission is to provide measurable impact on customer experience and BuilderWorks efficiencies through the use of scientific methods and processes. We quantify the impact of programs in terms of engagement and cost through data science studies. We own the model framework, where we deliver prospective insights and retrospective measurements of the effect that BuilderWorks programs have on builder experience. We partner with BuilderWorks programs to develop a principled and data driven methodology for quantifying the impact of programs on SDO.BASIC QUALIFICATIONS- 3+ years of building models for business application experience- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- Experience programming in Java, C++, Python or related language- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing ...

Have you ever ordered a product on Amazon and when that box with the smile arrived you wondered how it got to you so fast? Have you wondered where it came from and how much it cost Amazon to deliver it to you? If so, the WW Amazon Logistics, Business Analytics team is for you. We manage the delivery of tens of millions of products every week to Amazon’s customers, achieving on-time delivery in a cost-effective manner. We are looking for an enthusiastic, customer obsessed, Sr. Applied Scientist with good analytical skills to help manage projects and operations, implement scheduling solutions, improve metrics, and develop scalable processes and tools. The primary role of an Operations Research Scientist within Amazon is to address business challenges through building a compelling case, and using data to influence change across the organization. This individual will be given responsibility on their first day to own those business challenges and the autonomy to think strategically and make data driven decisions. Decisions and tools made in this role will have significant impact to the customer experience, as it will have a major impact on how the final phase of delivery is done at Amazon. Ideal candidates will be a high potential, strategic and analytic graduate with a PhD in (Operations Research, Statistics, Engineering, and Supply Chain) ready for challenging opportunities in the core of our world class operations space. Great candidates have a history of operations research, and the ability to use data and research to make changes. This role requires robust program management skills and research science skills in order to act on research outcomes. This individual will need to be able to work with a team, but also be comfortable making decisions independently, in what is often times an ambiguous environment.Responsibilities may include: - Develop input and assumptions based preexisting models to estimate the costs and savings opportunities associated with varying levels of network growth and operations - Creating metrics to measure business performance, identify root causes and trends, and prescribe action plans - Managing multiple projects simultaneously - Working with technology teams and product managers to develop new tools and systems to support the growth of the business - Communicating with and supporting various internal stakeholders and external audiencesBASIC QUALIFICATIONS- 10+ years of building machine learning models or developing algorithms for business application experience- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field, or Master's degree and 10+ years of industry or academic research experience- Knowledge of programming languages such as C/C++, Python, Java or Perl- Experience with neural deep learning methods and machine learning ...

The Automated Reasoning Group is looking for a Applied Scientist with expertise in programming language semantics and deductive verification techniques (e.g. Lean, Dafny) to deliver novel code reasoning capabilities at scale. You will be part of a larger organization that develops a spectrum of formal software analysis tools and applies them to software at all levels of abstraction from assembler through high-level programming languages. You will work with a team of world class automated reasoning experts to deliver code reasoning technology that is accessible to all developers.BASIC QUALIFICATIONS- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- Experience in patents or publications at top-tier peer-reviewed conferences or journals- Experience programming in Java, C++, Python or related language- Experience in automated reasoning techniques, such as SAT/SMT, deductive verification. ...

Are you inspired by invention? Is problem solving through teamwork in your DNA? Do you like the idea of seeing how your work impacts the bigger picture? Answer yes to any of these and you’ll fit right in here at Amazon Robotics. We are a smart team of doers that work passionately to apply cutting edge advances in robotics and software to solve real-world challenges that will transform our customers’ experiences in ways we can’t even imagine yet. We invent new improvements every day. We are Amazon Robotics and we will give you the tools and support you need to invent with us in ways that are rewarding, fulfilling and fun.Amazon Robotics is seeking Applied Science Interns and Co-ops with a passion for robotic research to work on cutting edge algorithms for robotics. Our team works on challenging and high-impact projects within robotics. Examples of projects include allocating resources to complete a million orders a day, coordinating the motion of thousands of robots, autonomous navigation in warehouses, identifying objects and damage, and learning how to grasp all the products Amazon sells. As an Applied Science Intern/Co-op at Amazon Robotics, you will be working on one or more of our robotic technologies such as autonomous mobile robots, robot manipulators, and computer vision identification technologies. The intern/co-op project(s) and the internship/co-op location are determined by the team the student will be working on.Please note that by applying to this role you would be considered for Applied Scientist summer intern, spring co-op, and fall co-op roles on various Amazon Robotics teams. These teams work on robotics research within areas such as computer vision, machine learning, robotic manipulation, navigation, path planning, perception, optimization and more. Learn more about Amazon Robotics: https://amazon.jobs/en/teams/amazon-roboticsBASIC QUALIFICATIONS- Currently enrolled in a Master's or PhD program in Computer Science, Robotics, Engineering, Machine Learning, Operations Research, Mathematics, or a related quantitative field- Degree program must be based in the United States with an expected graduation of December 2025 or later- Must be eligible for and available for full-time (40 hours per week) internship in person based out of the assigned office location for the whole duration of the internship/co-op- Relevant academic research or industry experience within Robotics, Computer Vision, Machine Learning, Optimization, Manipulation, Perception, Motion Planning and Controls, Movement, Autonomous Navigation, Path Planning, or related- Experience programming in Java, C++, Python, or related ...

Do you enjoy solving challenging problems and driving innovations in research? Are you seeking for an environment with a group of motivated and talented scientists like yourself? Do you want to create scalable optimization models and apply machine learning techniques to guide real-world decisions? Do you want to play a key role in the future of Amazon transportation and operations? Come and join us at Amazon's Modeling and Optimization team (MOP).Key job responsibilitiesAn Applied Scientist in the Modeling and Optimization (MOP) team - provides analytical decision support to Amazon planning teams via applying advanced mathematical and statistical techniques.- collaborates effectively with Amazon internal business customers, and is their trusted partner- is proactive and autonomous in discovering and resolving business pain-points within a given scope- is able to identify a suitable level of sophistication in resolving the different business needs- is confident in leveraging existing solutions to new problems where appropriate and is independent in designing and implementing new solutions where needed- is aware of the limitations of their proposed solutions and is proactive in communicating them to the business, and advances the application of sciences towards Amazon business problems by bringing new methods, ideas, and practices to the team and scientific community.A day in the life- Your will be developing model-based optimization, simulation, and/or predictive tools to identify and evaluate opportunities to improve customer experience, network speed, cost, and efficiency of capital investment.- You will quantify the improvements resulting from the application of these tools and you will evaluate the trade-offs between potentially competing objectives. - You will develop good communication skills and ability to speak at a level appropriate for the audience, will collaborate effectively with fellow scientists, software development engineers, and product managers, and will deliver business value in a close partnership with many stakeholders from operations, finance, IT, and business leadership.About the team- At the Modeling and Optimization (MOP) team, we use mathematical optimization, algorithm design, statistics, and machine learning to improve decision-making capabilities across WW Operations and Amazon Logistics.- We focus on transportation topology, labor and resource planning for fulfillment facilities, routing science, visualization research, data science and development, and process optimization.- We create models to simulate, optimize, and control the fulfillment network with the objective of reducing cost while improving speed and reliability.- We support multiple business lanes, therefore maintain a comprehensive and objective view, coordinating solutions across organizational lines where possible.BASIC QUALIFICATIONS- 3+ years of building models for business application experience- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- Experience in patents or publications at top-tier peer-reviewed conferences or journals- Experience programming in Java, C++, Python or related language- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing ...

Do you have a passion for diving deep to uncover key insights that drive critical business decisions? If yes, the Marketing Incrementality and Decision Support (MIDS) team is looking for talented individuals with your enthusiasm and skills to work as part of the team. We are looking for a Senior Research Scientist with marketing measurement, experimentation and causal inference background, who is curious, driven, and passionate about marketing insights and analytics.The Customer Behavior Analytics (CBA) organization owns Amazon’s insights pipeline, from data collection to deep analytics. We aspire to be the place where Amazon teams come for answers, a trusted source for data and insights that empower our systems and business leaders to make better decisions. Our outputs shape Amazon product and marketing teams’ decisions and thus how Amazon customers see, use, and value their experience. MIDS’s mission is to make Amazon’s marketing the most measurably effective in the world. Our long-term objective is to measure the incremental impact of all Amazon’s marketing investments on consumer perceptions, actions, and sales. This requires measuring Amazon’s marketing comparably and consistently across channels, business teams and countries using a comprehensive approach that integrates all Paid, Owned and Earned marketing activity. As the experts on marketing performance, we will lead the Amazon worldwide marketing community by providing critical cross-country insights that can power marketing best practices and tenets globally.In this role, you will be a technical leader to design and run Randomized Control Trials and large-scale online experiments to measure the performance of Amazon's marketing cross all marketing channels, geographies and businesses. You will lead scientists and engineers to develop both experimental and observational models to understand customer behavior and how customers respond to Amazon’s advertisement. You will drive innovation to combine experiment results with observational model outputs to build more accurate marketing measurement solutions. You will lead strategic measurement science initiatives in MIDS and across various marketing teams, scaling experimentation and development and deployment of the measurement science models, real-time inference, and cross-channel orchestration.As a successful Research Scientist, you are an analytical problem solver who enjoys diving into data, leads problem solving, guides development of new frameworks, writes code, is excited about investigations and algorithms, and can credibly interface between technical teams and business stakeholders. You are an expert in causal inference and experiment design, preferably has experience leveraging experimental model to calibrate observational model. You are a hands-on innovator who can contribute to advancing Marketing measurement technology in a B2C and B2B environment, and push the limits on what’s scientifically possible with a razor sharp focus on measurable customer and business impact. You will coach and guide scientists in the team to grow the team’s talent and scale the impact of your work. You will also communicate verbally and in writing to business customers and leadership team with various levels of technical knowledge, educating them about our systems, as well as sharing insights and recommendationsBASIC QUALIFICATIONS- 3+ years of investigating the feasibility of applying scientific principles and concepts to business problems and products experience- PhD, or Master's degree and 5+ years of quantitative field research experience- Experience with big data technologies such as AWS, Hadoop, Spark, Pig, Hive etc.- Experience communicating qualitative research methods and findings to non-qualitative researchers ...

Amazon’s Modeling and Optimization (MOP) Team is looking for a passionate individual with strong optimization and analytical skills to join us in the endeavor of designing and planning the most complex supply chain in the world.The team is responsible for optimizing the global supply chain for Amazon.com and ensuring that the company is able to inbound goods from seller and vendors, transport them to their target fulfillment center, and deliver to our customers as quickly, accurately, and cost effectively as possible. We work on problems ranging from network design to assortment optimization, in order to support strategic decisions. It is a terrific opportunity to have a direct impact in the business while pushing the boundaries of science.Key job responsibilitiesWe are seeking an experienced scientist who has solid background in Operations Research, Operations Management, Applied Mathematics or other similar domain.In this role, you will develop models and solution algorithms that are innovative and scalable to solve new challenges in the network design space. You will collaborate with other scientists across teams to create integrated solutions that improve fulfillment speed and minimize end-to-end cost. You have deep understanding of business challenges and will provide scientific analysis to support business decision using a range of methodologies. You will also work with engineering teams to identify new data requirements, deploy new models or simplifying existing processes.About the teamhttps://www.aboutamazon.com/news/innovation-at-amazon/how-artificial-intelligence-helps-amazon-deliverBASIC QUALIFICATIONS- 3+ years of building models for business application experience- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- Experience in patents or publications at top-tier peer-reviewed conferences or journals- Experience programming in Java, C++, Python or related language- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing ...