Careers

The Central Science Team within Amazon’s People Experience and Technology org (PXTCS) uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, well-being, and the value of work to Amazonians. We are an interdisciplinary team, which combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal. We are looking for an economist with expertise in applying causal inference methods, especially experimental design to topics in labor, personnel, education, or behavioral economics. We are particularly interested in candidates with experience applying these skills to strategic problems with significant business and/or social policy impact. The candidate will work with economists and engineers to estimate and validate their models on large scale data, and will help business partners turn the results of their analysis into policies, programs, and actions that have a major impact on Amazon’s business and its workforce. We are looking for a creative thinker who can combine a strong economic toolbox with a desire to learn from others, and who knows how to execute and deliver on big ideas. Ideal candidates will own key inputs to all stages of research projects, including model development, survey administration, experimental design, and data analysis. They will be customer-centric, working closely with business partners to define key research questions, communicate scientific approaches and findings, listen to and incorporate partner feedback, and deliver successful solutions.

About Amazon Health Amazon Health’s mission is to make it dramatically easier for customers to access the healthcare products and services they need to get and stay healthy. Towards this mission, we (Health Storefront and Shared Tech) are building the technology, products and services, that help customers find, buy, and engage with the healthcare solutions they need. Job summary We are seeking an exceptional Senior Applied Scientist to join a team of experts in the field of machine learning, and work together to break new ground in the world of healthcare to make personalized and empathetic care accessible, convenient, and cost-effective. We leverage and train state-of-the-art large-language-models (LLMs) and develop entirely new experiences to help customers find the right products and services to address their health needs. We work on machine learning problems for intent detection, dialogue systems, and information retrieval. You will work in a highly collaborative environment where you can pursue both near-term productization opportunities to make immediate, meaningful customer impacts while pursuing ambitious, long-term research. You will work on hard science problems that have not been solved before, conduct rapid prototyping to validate your hypothesis, and deploy your algorithmic ideas at scale. You will get the opportunity to pursue work that makes people's lives better and pushes the envelop of science. #everydaybetter Key job responsibilities - Translate product and CX requirements into science metrics and rigorous testing methodologies. - Invent and develop scalable methodologies to evaluate LLM outputs against metrics and guardrails. - Design and implement the best-in-class semantic retrieval system by creating high-quality knowledge base and optimizing embedding models and similarity measures. - Conduct tuning, training, and optimization of LLMs to achieve a compelling CX while reducing operational cost to be scalable. A day in the life In a fast-paced innovation environment, you work closely with product, UX, and business teams to understand customer's challenges. You translate product and business requirements into science problems. You dive deep into challenging science problems, enabling entirely new ML and LLM-driven customer experiences. You identify hypothesis and conduct rapid prototyping to learn quickly. You develop and deploy models at scale to pursue productizations. You mentor junior science team members and help influence our org in scientific best practices. About the team We are the Health AI team at HST (Health Store and Technology). The team consists of exceptional ML Scientists with diverse background in healthcare, robotics, customer analytics, and communication. We are committed to building and deploying the most advanced scientific capabilities and solutions for the products and services at Amazon Health.

Our customers have immense faith in our ability to deliver packages timely and as expected. A well planned network seamlessly scales to handle millions of package movements a day. It has monitoring mechanisms that detect failures before they even happen (such as predicting network congestion, operations breakdown), and perform proactive corrective actions. When failures do happen, it has inbuilt redundancies to mitigate impact (such as determine other routes or service providers that can handle the extra load), and avoids relying on single points of failure (service provider, node, or arc). Finally, it is cost optimal, so that customers can be passed the benefit from an efficiently set up network. Amazon Shipping is hiring Applied Scientists to help improve our ability to plan and execute package movements. As an Applied Scientist in Amazon Shipping, you will work on multiple challenging machine learning problems spread across a wide spectrum of business problems. You will build ML models to help our transportation cost auditing platforms effectively audit off-manifest (discrepancies between planned and actual shipping cost). You will build models to improve the quality of financial and planning data by accurately predicting ship cost at a package level. Your models will help forecast the packages required to be pick from shipper warehouses to reduce First Mile shipping cost. Using signals from within the transportation network (such as network load, and velocity of movements derived from package scan events) and outside (such as weather signals), you will build models that predict delivery delay for every package. These models will help improve buyer experience by triggering early corrective actions, and generating proactive customer notifications. Your role will require you to demonstrate Think Big and Invent and Simplify, by refining and translating Transportation domain-related business problems into one or more Machine Learning problems. You will use techniques from a wide array of machine learning paradigms, such as supervised, unsupervised, semi-supervised and reinforcement learning. Your model choices will include, but not be limited to, linear/logistic models, tree based models, deep learning models, ensemble models, and Q-learning models. You will use techniques such as LIME and SHAP to make your models interpretable for your customers. You will employ a family of reusable modelling solutions to ensure that your ML solution scales across multiple regions (such as North America, Europe, Asia) and package movement types (such as small parcel movements and truck movements). You will partner with Applied Scientists and Research Scientists from other teams in US and India working on related business domains. Your models are expected to be of production quality, and will be directly used in production services. You will work as part of a diverse data science and engineering team comprising of other Applied Scientists, Software Development Engineers and Business Intelligence Engineers. You will participate in the Amazon ML community by authoring scientific papers and submitting them to Machine Learning conferences. You will mentor Applied Scientists and Software Development Engineers having a strong interest in ML. You will also be called upon to provide ML consultation outside your team for other problem statements. If you are excited by this charter, come join us!

We are a part of Amazon Alexa Devices organization with the mission “delight customers through contextual and personalized proactive experiences that keep customers informed, engaged, and productive without cognitive burden”. We are developing an advanced system using Large Language Model (LLM) technologies to deliver engaging, intuitive, and adaptive content recommendations across all Amazon surfaces. We aim to facilitate seamless reasoning and customer experiences, surpassing the capabilities of previous machine learning models. We are looking for a passionate, talented, and resourceful Applied Scientist in the field of Natural Language Processing (NLP), Recommender Systems and/or Information Retrieval, to invent and build scalable solutions for a state-of-the-art context-aware speech assistant. A successful candidate will have strong machine learning background and a desire to push the envelope in one or more of the above areas. The ideal candidate would also enjoy operating in dynamic environments, be self-motivated to take on challenging problems to deliver big customer impact, shipping solutions via rapid experimentation and then iterating on user feedback and interactions. Key job responsibilities As an Applied Scientist on the team, you will collaborate with other applied scientists and engineers to develop novel algorithms to enable timely, relevant and delightful recommendations and conversations. 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. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in the state of art.

Are you interested in building state-of-the-art machine learning systems for the most complex, and fastest growing, transportation network in the world? If so, Amazon has the most exciting, and never-before-seen, challenges at this scale (including those in sustainability, e.g. how to reach net zero carbon by 2040). Amazon’s transportation systems get millions of packages to customers worldwide faster and cheaper while providing world class customer experience – from online checkout, to shipment planning, fulfillment, and delivery. Our software systems include services that use tens of thousands of signals every second to make business decisions impacting billions of dollars a year, that integrate with a network of small and large carriers worldwide, that manage business rules for millions of unique products, and that improve experience of over hundreds of millions of online shoppers. As part of this team you will focus on the development and research of machine learning solutions and algorithms for core planning systems, as well as for other applications within Amazon Transportation Services, and impact the future of the Amazon delivery network. Current research and areas of work within our team include machine learning forecast, uncertainty quantification, planning systems, model interpretability, graph neural nets, among others. We are looking for a Machine Learning Scientist with a strong academic background in the areas of machine learning, time series forecasting, and/or optimization. At Amazon, we strive to continue being the most customer-centric company on earth. To stay there and continue improving, we need exceptionally talented, bright, and driven people. If you'd like to help us build the place to find and buy anything online, and deliver in the most efficient and greenest way possible, this is your chance to make history. About the team The EU ATS Science and Technology (SnT) team owns scalable algorithms, models and systems that improve customer experience in middle-mile. We work backwards from Amazon's customers aiming to make transportation faster, cheaper, safer, more reliable and ecologically sustainable.

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 ML 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 team for India Consumer Businesses. Machine Learning, Big Data and related quantitative sciences have been strategic to Amazon from the early years. Amazon has been a pioneer in areas such as recommendation engines, ecommerce fraud detection and large-scale optimization of fulfillment center operations. As Amazon has rapidly grown and diversified, the opportunity for applying machine learning has exploded. We have a very broad collection of practical problems where machine learning systems can dramatically improve the customer experience, reduce cost, and drive speed and automation. These include product bundle recommendations for millions of products, safeguarding financial transactions across by building the risk models, improving catalog quality via extracting product attribute values from structured/unstructured data for millions of products, enhancing address quality by powering customer suggestions We are developing state-of-the-art machine learning solutions to accelerate the Amazon India growth story. Amazon India is an exciting place to be at for a machine learning practitioner. We have the eagerness of a fresh startup to absorb machine learning solutions, and the scale of a mature firm to help support their development at the same time. As part of the India Machine Learning team, you will get to work alongside brilliant minds motivated to solve real-world machine learning problems that make a difference to millions of our customers. We encourage thought leadership and blue ocean thinking in ML. Key job 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, develop, evaluate and deploy, innovative and highly scalable ML models Work closely with software engineering teams to drive real-time model implementations Work closely with business partners to identify problems and propose machine learning solutions Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model maintenance Work proactively with engineering teams and product managers to evangelize new algorithms and drive the implementation of large-scale complex ML models in production Leading projects and mentoring other scientists, engineers in the use of ML techniques About the team International Machine Learning Team is responsible for building novel ML solutions that attack India first (and other Emerging Markets across MENA and LatAm) problems and impact the bottom-line and top-line of India business. Learn more about our team from https://www.amazon.science/working-at-amazon/how-rajeev-rastogis-machine-learning-team-in-india-develops-innovations-for-customers-worldwide

Excited by Big Data, Machine Learning, and Predictive Software? Interested in creating new state-of-the-art solutions using Machine Learning and Data Mining techniques on Terabytes of Data? At Amazon Global Logistics (AGL), our vision is to become the carrier of choice for all of our Selling Partners' cross-border shipping needs, offering a complete set of end-to-end cross-border solutions from key manufacturing hubs to footprint countries, supporting businesses that use Amazon to grow their business globall Key job responsibilities - Utilize machine learning, data mining, and statistical techniques to create new, scalable solutions for business problems. - Analyze and extract relevant information from business data to help automate and optimize key processes. - Design, develop, and evaluate highly innovative models for predictive learning. - Establish scalable, efficient, automated processes for large-scale data analyses, model development, model validation, and model implementation. - Research and implement novel machine learning and statistical approaches. A day in the life As a Data Scientist III in the Business Insight team at Amazon Global Logistics, you will be responsible for developing state-of-the-art large-scale Machine Learning Services involving vast amounts of data and macroeconomic inputs. Your primary focus will be to produce robust forecasts to aid operational excellence and continue improving the customer experience. You will collaborate with cross-functional teams to understand seller behaviors and their impacts on demand generation, demand forecasting, pricing strategies, and asset utilization, especially in areas with variable demand. Your expertise in machine learning, data mining, and statistical techniques will be crucial in creating scalable solutions that drive business impact. About the team The Business Insight team at Amazon Global Logistics is dedicated to leveraging data and advanced analytics to drive operational excellence and enhance the customer experience. As we expand our global logistics operations, the need for solid understanding of seller behaviors, demand forecasting, pricing strategies, and asset utilization becomes increasingly vital. Our team comprises talented and experienced professionals who are passionate about applying innovative machine learning techniques to real-world problems and converting them into highly business-impacting solutions. We foster a collaborative environment that encourages creativity, continuous learning, and a strong commitment to delivering exceptional results. Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan Learn more about our benefits here: https://www.amazon.jobs/en/internal/benefits/us-benefits-and-stock

Amazon’s AGI Information is seeking an exceptional Senior Applied Scientist to drive science advancements in the Amazon Knowledge Graph team (AKG). AKG is re-inventing knowledge graphs for the LLM-era, optimizing for LLM grounding and other LLM-based customer experiences. At the same time, AKG is innovating to utilize LLMs in the knowledge graph construction pipelines to overcome obstacles that traditional technologies could not overcome. As a member of the AKG Science team, you will have the opportunity to work on interesting cutting edge problems with immediate customer impact. The team is addressing challenges in automating gap detection, data ingestion, fact verification, query optimization and entity resolution. Your initial focus will be on entity resolution, and you will also have the opportunity to work with scientists working on the other challenges, and with the engineering teams that deliver the science advancements to our customers. A successful candidate has a strong machine learning and LLM background, is a master of state of the art techniques, has a strong publication record, has a desire to push the envelope in one or more of the above areas, and has a track record of delivering to customers. The ideal candidate enjoys operating in dynamic environments, is self-motivated to take on new challenges, and enjoys working with customers, stakeholders and engineering teams to deliver big customer impact, shipping solutions via rapid experimentation and then iterating on user feedback and interactions. Key job responsibilities As a Senior Applied Scientist, you will leverage your technical expertise and experience to demonstrate leadership in tackling large complex problems. You will collaborate with applied scientists and engineers to develop novel algorithms and modeling techniques to build the knowledge graph that delivers fresh factual knowledge to our customers, and that automates the knowledge graph construction pipelines to scale to many billions of facts. Your first responsibility will be to solve entity resolution to enable conflating facts from multiple sources into a single graph entity for each real world entity. You will develop generic solutions that work fo all classes of data in AKG (e.g., people, places, movies, etc.), that cope with sparse, noisy data, that scale to hundreds of millions of entities, and that can handle streaming data. You will define a roadmap to make progress incrementally and you will insist on scientific rigor, leading by example.

Amazon Next Generation Developer Experience (NGDE) Organization is looking for world class scientists and engineers to join its team working on AI4Code, LLM, and natural language processing. This group is entrusted with developing core algorithms/capabilities for Amazon Q Developer. At NGDE you will invent, implement, and deploy state of the art AI algorithms and systems for developers. You will build prototypes and explore conceptually new large scale AI solutions. You will interact closely with our customers and with the academic community. You will be at the heart of a growing and exciting focus area for AWS and work with other acclaimed engineers and world famous scientists. About the team 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, including support for customers who require specialized security solutions for their cloud services. 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 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.

The GMAC Econ team is looking for a data scientist to support strategic projects in the Prime Video business. Prime Video provides value to our customers as both a key Prime membership benefit and separately as a retail outlet for digital downloads and streams of top TV and Movie titles. As an data scientist in GMAC Econ focusing on Prime Video, you will be responsible for understanding the value that the business creates for our customers and for Amazon’s extensive ecosystem. This role requires an individual with strong quantitative modeling skills and the ability to apply statistical/machine learning, causal analysis and experimental design methods to large amount of individual level data. The candidate should have strong communication skills, be able to work closely with stakeholders and translate data-driven findings into actionable insights. The successful candidate will be a self-starter comfortable with ambiguity, with strong attention to detail and ability to work in a fast-paced and ever-changing environment. Key job responsibilities * Build, validate, and scale analytic solutions using state of the art tools based on large datasets * Conduct statistical/machine learning analyses, or design experiments to measure the value of the business and its many features * Partner closely with Business, Finance, Science, and Tech partners from ideation to implementation of production solutions * Independently identify new opportunities for leveraging economic insights and models that drive a better understanding of the Video business * Write both technical white papers and business-facing documents to clearly explain complex technical concepts to partner teams and leaders About the team We are a central team of Economists, Data Scientists, and Engineers in Global Media, Advertising and Corporate Development (GMAC) finance that focuses on the development of disruptive ideas and novel economic tools to help support the growth and long term economic value of GMAC and broader Amazon. We also provide tactical support where we are uniquely positioned to do so because of our expertise or independence. We prioritize projects based on expected impact, taking into account the feasibility of implementation by our business partners, or if it makes sense for us to build it ourselves.