Careers

The Artificial General Intelligence (AGI) team is looking for a highly-skilled Senior Applied Scientist, to lead the development and implementation of cutting-edge algorithms and push the boundaries of efficient inference for Generative Artificial Intelligence (GenAI) models. As a Senior Applied Scientist, you will play a critical role in driving the development of GenAI technologies that can handle Amazon-scale use cases and have a significant impact on our customers' experiences. Key job responsibilities - Design and execute experiments to evaluate the performance of different decoding algorithms and models, and iterate quickly to improve results - Develop deep learning models for compression, system optimization, and inference - Collaborate with cross-functional teams of engineers and scientists to identify and solve complex problems in GenAI - Mentor and guide junior scientists and engineers, and contribute to the overall growth and development of the team

How can Amazon improve the advertising experience for customers around the world? How can we help advertisers and customers find each other in a meaningful way? Amazon Advertising creates and transforms the connection between retailers/service providers and customers. Our teams strive to reinvent the way advertisers and agencies build brands and drive performance in their advertising. By using Amazon's foundation in e-commerce, we help brands connect with the right customers through creative solutions and formats across screens and devices, and in the physical world. Amazon Advertising seeks an Applied Scientist with strong Machine Learning engineering skills to join the ADSP engineering team split across Edinburgh and London. We make Guidance products that help optimise our customer's advertising campaign workflows and performance. As a scientist on the team, you will be involved in every aspect of the process - from idea generation, business analysis and scientific research, through to development and deployment of advanced models - giving you a real sense of ownership. The systems that you help to build will operate at massive scale to advertising customers around the world. Our ideal candidate is an experienced ML scientist who has a track-record of performing analysis, applying statistical techniques and building robust ML models to solve real business problems, who has great leadership and communication skills, and who is motivated to achieve results in a fast-paced environment. Key job responsibilities Rapidly design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both quantitative analysis and business judgment. Collaborate with software engineering teams to integrate successful experimental results into large-scale, highly complex Amazon production systems. Report results in a manner which is both statistically rigorous and compellingly relevant, exemplifying good scientific practice in a business environment. Promote the culture of experimentation and applied science at Amazon.

The Senior Applied Science Manager owns the complete science mission and team for Advertising Trust. We’re a global organization that is highly matrixed and this role reports directly to the VP of Advertising Trust. Science is not just at the core of what Advertising Trust does, but it’s essential. We have one of the largest and most highly complex yet important missions and the work is not going away, instead it’s growing with nuance and challenges with the advent of GenAI, et. al. You will apply state of the art technologies across computer vision, LLM training and application, etc. to deliver on this mission. It requires high judgment, self-direction and curiosity to achieve truly world leading innovation. The role will present regularly to senior leadership, providing opportunities to gain their unique insight, and advocate for cross-organization investments for optimal decision-making. This is a fun, high energy role that will provide opportunities for growth for even the most seasoned executive. Key job responsibilities • You must be a highly collaborative leader who thrives on earning trust through transparency. • You must be able to develop bold visions with highly specific roadmaps to achieve those visions. • You must be a vocal advocate for your team and science in general and “lean in” to conversations. • You must be up to travel frequently for this role, including to the US to meet with key business leaders and partners. • Hire and develop entire team all the way from the Principal level to new hire all elements of the Science team. • Taking full service ownership of your teams including developing research and engineering (product roadmaps), developing and tracking relevant metrics, and ensuring system performance. • Coaching and developing scientists to maintain standards and to drive career growth for your direct reports. • Building a team culture around technical excellence and strong delivery. About the team Advertising Trust (AT) is at the center of Amazon Ads, one of Amazon’s fastest growing businesses. Every ad that flows through our Amazon systems, or is presented on one of our owned and operated sites, needs to adhere to the policies that AT creates. These policies simplify the complex regulatory, legal, regional, cultural and customer expectations in over 30 countries today. All of these ads need to be properly approved or rejected the first time and within SLA. There should be no ambiguity as to why the ad was approved or rejected from the perspective of the Advertiser or Publisher and the ad should be able to reach its optimal audience. If AT is doing a great job, the ecosystem is efficient and we can ensure a great shopper experience.

The Smart Home team is focused on making Alexa the user interface for the home. From the simplest voice commands (turn on the lights, turn down the heat) to use cases spanning home security, home entertainment, and the home environment, we are evolving Alexa into intelligent, indispensable companion that automates daily routines, simplifies interaction with appliances and electronics, and alerts when something unusual is detected. You will be part of a team delivering features that are highly anticipated by media and well received by our customers. As a Senior Applied Scientist, you will work with other scientists and software developers to design and build the next generation of Smart Home voice control using the latest Large Language Models. And, you will have the satisfaction of working on a product your friends and family can relate to, and want to use every day. Key job responsibilities Developing new inference and training techniques to improve the performance of Large Language Models for Smart Home control and Automation. Developing robust techniques for synthetic data generation for training large models and maintaining model generalization. Mentoring junior scientists to improve their skills, knowledge, and their ability to get things done. About the team We are a team of Scientists, Machine Learning Engineers, and Software Developers that work together to make Alexa more insightful and proactive through ambient intelligence - with features like Alexa Hunches that automatically control Smart Home devices. We are interdisciplinary and we act like it -- we ask each other questions and value our different perspectives.

The Alexa Smart Home team is focused on making Alexa the user interface for the home. From the simplest voice commands (turn on the lights, turn down the heat) to use cases spanning home security, home entertainment, and the home environment; we are evolving Alexa into an intelligent, indispensable companion that automates daily routines, simplifies interaction with appliances and electronics, and alerts when something unusual is detected. You can be part of a team delivering features that are highly anticipated by media and well received by our customers. As an Applied Scientist, you will work with other scientists and software developers to design and build the next generation of Smart Home experiences using the latest Large Language Models (LLMs). You will build products that your friends and family, along with millions of Alexa Smart Home customers use every day. Key job responsibilities - Develop new inference and training techniques to improve the performance of LLMs for Smart Home control and automation - Develop robust techniques for synthetic data generation for training large models and maintaining model generalization - Mentoring junior scientists to improve their skills, knowledge, and their ability to get things done About the team We are a team of Scientists, Machine Learning Engineers, and Software Developers that work together to make Alexa more insightful and proactive through ambient intelligence, with features like Alexa Hunches that automatically control Smart Home devices. We are interdisciplinary and we act like it. We ask each other questions and value our different perspectives.

Are you fascinated by the power of Natural Language Processing (NLP) and Large Language Models (LLM) to transform the way we interact with technology? Are you fascinated by the use of Generative AI to build an advertiser facing solution that predict problems and coach users while they solve real word problems? Are you passionate about applying advanced machine learning techniques to solve complex challenges in the customer service space? If so, Amazon's Support Product & Services (SP&S) team has an exciting opportunity for you as an Applied Scientist. Key job responsibilities • Apply your expertise in LLM models to design, develop, and implement scalable machine learning solutions that address complex language-related challenges in the advertising support center domain. • Use Transformers and apply other NLP techniques like Sentence embeddings, Dimensionality reduction, clustering and topic modeling to identify customer intents and utterances. • Use services like AWS Lex, AWS Bedrock etc. to develop advertising facing solutions • Work closely with teams of scientists and software engineers to drive real-time model implementations and deliver novel and highly impactful solutions. • Automating feedback loops for algorithms in production. • Setup and monitor alarms to detect anomalous data patterns and perform root cause analyses to explain and address them. • Be a member of the Amazon-wide Machine Learning Community, participating in internal and external MeetUps, Hackathons and Conferences. A day in the life You will work closely with a cross functional team of Software Engineers, Product Owners, Data Scientists, and Contact Center experts. You will research and investigate the latest options in industry to apply machine learning and generative AI to real world problems. You will work backwards from customer problems and collaborate with stakeholders to determine how to scale new technology and integrate with complicated help channels used by advertisers everyday. About the team SP&S team provides solutions and libraries that are leveraged by teams all across Amazon Advertising to provide timely and personalized help. The team aims to predict Advertisers problems and proactively surface intelligent guidance to customers at the right time. As a AS, you will help the team to achieve its vision of building and implementing the next generation of Contact Center technology. You will build/leverage LLMs to train them on advertising support domain knowledge and work shoulder to shoulder with stakeholders to externalize to users in novel ways.

Amazon Japan Store Tech (JST) Science team serves as the core science division of JP Store Tech, with the vision to enable and accelerate the best-in-class CX through state-of-the-art machine learning technologies. This team owns the science vision definition, science roadmap planning, and science solution delivery in key business areas in Japan including Search, Customer Growth and Engagement, Personalization and Delivery. As the Sr. Applied Science Manager, you will manager the teams of scientists (applied scientists, data scientists) and machine learning engineers where the business opportunity or overall strategy may not yet be defined. You need to create the science long-term vision and roadmap across multiple business domains. Your team will design, implement and deliver science models on Amazon site, helping millions of customers every day to find quickly what they are looking for. Key job responsibilities * Leads team(s) performing strategically important scientific analyses to identify technology gaps and business opportunities. * Leads team(s) driving the design and delivery of solutions or systems that address significantly complex science problems and tooling efforts, decisions, and escalations. * Communicates and drives strategic initiatives (3-5 year). Critical inputs into OP1/OP2. May be actively involved with the external scientific community *Build a science publication strategy (what to publish, where and when). Determines when to establish a program or make a case for resources. A day in the life Your benefits include: * Working on a high-impact, high-visibility product, with your work improving the experience of millions of customers * The opportunity to use (and innovate) state-of-the-art ML methods to solve real-world problems with tangible customer impact * Being part of a growing team where you can influence the team's mission, direction, and how we achieve our goals

Amazon Japan is seeking an experienced Sr. Data Scientist to join our growing team. In this critical role, you will leverage your strong quantitative and analytical skills to drive data-driven insights that shape our FMCG (fast-moving consumer goods) business and other key strategic initiatives. Your responsibilities will include: - Solving complex, ambiguous business problems using appropriate statistical methodologies, modeling techniques, and data science best practices to lead business insights for FMCG business growth. You will work closely with cross-functional partners to translate business requirements into actionable data science solutions. - Designing and implementing scalable, reliable, and efficient data pipelines to extract valuable insights from diverse data sources. This includes making appropriate trade-offs between short-term and long-term needs. - Communicating your findings and recommendations clearly and persuasively to technical and non-technical stakeholders. You will document your work to the highest standards and ensure your solutions have a measurable impact on the business. - Mentoring and developing more junior data scientists on your team. You will actively participate in the hiring process and contribute to the growth of Amazon's data science community. - Staying abreast of the latest advancements in data science and applying innovative techniques where appropriate to tackle challenging business problems.

At Amazon, we're committed to pioneering new frontiers in customer experience, and Fashion Tech is at the forefront of this mission. Our programs and technologies are revolutionizing how customers interact with fashion products, presenting unique challenges and opportunities for quantifying their economic impact. We're seeking a highly experienced Principal Economist with expertise in causal modeling to lead our efforts in understanding the economic impact of our efforts in this dynamic space. Over the years, teams across Amazon have built systems that can value content and even optimize what is shown based on relevant ‘value’ metrics. However, understanding attribution and program incrementality continue to be challenges that require tying the business context with the most relevant methodology from an array of possible ones. The person in this role will work with finance, CBA and business owners to define the right metrics and methodologies to compute attributed and incremental value of programs and features, while leveraging existing frameworks wherever applicable. We want to answer questions like “If this program didn’t exist, what is the total economic value to Amazon that we would stand to lose?” and “What is the ongoing business impact of this CX post-launch?”. Key job responsibilities - Spearhead collaborative efforts with finance, CBA (Cost-Benefit Analysis), and business teams to define robust metrics and methodologies for measuring the attributed and incremental value of Fashion Tech programs and features. - Develop advanced frameworks and models to assess the causal economic impact of content, programs, and customer experience enhancements throughout the customer purchase funnel. - Lead the resolution of complex challenges related to content attribution and program incrementality, leveraging existing systems and methodologies while exploring innovative approaches where necessary. - Conduct in-depth economic analyses to address critical business questions, such as estimating the economic value of key programs and evaluating the ongoing business impact of post-launch customer experience improvements. - Drive cross-functional collaboration with data scientists, economists, and business leaders to integrate economic insights into strategic decision-making processes and shape future initiatives. - Stay at the forefront of industry trends, economic research, and best practices in causal modeling and econometric techniques, continuously enhancing our methodologies and frameworks to ensure relevance and effectiveness. About the team The Fashion Tech organization has a mission to make Amazon the most-loved fashion destination globally through technology by building novel experiences that bring a diverse breadth of customers to shop fashion in the Amazon store. The Fashion Intelligence team improves the speed, accuracy, and standards of data driven decisions across all programs within Fashion Tech. As a central analytics team, our goal is to break silos and identify interconnectedness across Fashion Tech programs, keeping the customer at the center.

As an Applied Scientist, you will lead and support the invention of foundation models for robotic perception and manipulation. You will collaborate with a team of scientists and engineers to develop new machine learning architectures and training methods and to adapt and fine-tune models for a variety of robotic tasks. You will work with platform teams to integrate these new models into existing and future robotic systems, evaluate their use in deployed systems, and invent new ways for these systems to improve over time. Your work and insights will help define the long-term strategy for the role of AI for computer vision and learned behaviors in Amazon’s autonomous robots. Key job responsibilities - Research vision - Where should we be focusing our efforts in this rapidly developing field - Research delivery – Proving/dis-proving strategies in offline data or in the lab to maximize progress and deliver results - Production studies - Insights from production systems and data A day in the life Every day you will be interacting with scientists and engineers based in Seattle, Boston, and Arlington. You will be interfacing with engineers and scientists building and deploying production systems, and you will interact with the team managing our data lake. You will be connecting the dots by finding the most effective way to exploit our data to impact production. Communication is essential, as well as making quick decisions and moving ahead as quickly as possible to try out ideas, discard the ones that don’t work, and leaning into those that do. 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 If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply! About the team Our team is small but our ambitions are big. We are primarily focused on building perception systems using computer vision and machine learning, but our outputs are grounded in the real physical world. We move fluidly between vision, robotics, and machine learning with a large dose of vision-language foundation models in the mix. Above all, we value creativity, effective communication, and an ability to provide the insights that will move us toward our ambitious goals.