Careers

Have you ever wondered how Amazon predicts when your order will arrive and how we ensure that it actually arrives on at the promised date/time? Have you wondered where all those Amazon semi-trucks on the road are headed? Are you passionate about increasing efficiency and reducing carbon footprint? Does the idea of having worldwide impact on Amazon's logistics network including our planes, trucks, and vans sound exciting to you? If so, then we want to talk with you! At Amazon's Supply Chain Optimization Technologies (SCOT), we are tasked with optimizing the fulfilment on customer orders so that we fulfil all orders worldwide in the most intelligent manner while ensuring Amazon customers get their orders on time. Amazon Fulfillment Planning & Execution (FPX) Science team within SCOT- Fulfilment Optimization group is seeking Manager Research Science with expertise in Machine Learning and/or Optimization and a proven record of leading scientists and solving business problems through scalable ML solutions. FPX Science tackles some of the most mathematically complex challenges in transportation planning and execution space to improve Amazon's operational efficiency worldwide. We own Amazon’s global fulfilment center and transportation planning and execution. The team also owns the short-term network planning and execution that determines the optimal flow of customer orders through Amazon fulfilment network. This includes developing sophisticated math models and controllers that assign orders to fulfilment centers to be picked and packed and then planning the optimal ship method in terms of cost, speed and carbon impact to deliver to the customer. These plans drive downstream decisions that are in the billions of dollars at Amazon Scale worldwide. The systems we build are entirely in-house, and are on the cutting edge of both academic and applied research in large scale supply chain planning, optimization, machine learning and statistics. These systems operate at various scales, from real-time decision system that completes thousands of transactions per seconds, to large scale distributed system that optimize Amazon’s fulfilment network. As Amazon continues to build and expand the first party delivery network, this role will be critical to realize this vision. Your team and tech solution will have large impacts to the physical supply chain of Amazon, and play a key role in improving Amazon consumer business’s long-term profitability. If you are interested in diving into a multi-discipline, high impact space this is the team for you. We’re looking for a passionate, results-oriented, and inventive Scientist who can lead from the front towards developing and deploying ML models for our outbound transportation planning systems. In addition, you will be working on design, development and evaluation of highly innovative ML models for solving complex business problems in the area of outbound transportation planning systems. The position is located at Bellevue, WA, just next to Seattle with beautiful outdoors and great city life. Watch http://bit.ly/amazon-scot to get the big picture. Key job responsibilities As a Manager of Research Science within FPX Science team, you will lead a team of research and applied scientists towards designing and deploy solutions that will likely draw from a range of scientific areas such as supervised, semi-supervised and unsupervised learning, reinforcement learning, advanced statistical modeling, and graph models. You will have an opportunity to be on the forefront of supply chain thought leadership by working on some of the most difficult problems in the industry, with some of the best product managers, research scientists, statisticians, and software engineers to integrate scientific work into production systems. You will bring deep technical expertise in the area of Machine Learning, and will play an integral part in building Amazon's Fulfillment Optimization systems. Other responsibilities include: * Lead a team of research and applied scientists towards design, development and evaluation of highly innovative ML models for solving complex business problems. * Technically lead and mentor the scientists on the team. * Research and apply the latest ML techniques and best practices from both academia and industry. * Use and analytical techniques to create scalable solutions for business problems. * Work closely with software engineering teams to build model implementations and integrate successful models and algorithms in production systems at very large scale. * Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation. A day in the life In this critical 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 supply chain globally. As a science manager on the team, you will engage in all facets of the process from ideation, business analysis and scientific research to development and deployment of advanced models. We are seeking someone who wants to lead projects that require innovative thinking and deep technical problem-solving skills to create production-ready machine learning solutions. A successful candidate is able to quickly approach large ambiguous problems, turn high-level business requirements into mathematical models, identify the right solution approach, and contribute to the software development for production systems. Successful candidates must thrive in fast-paced environments, which encourage collaborative and creative problem solving, be able to measure and estimate risks, constructively critique peer research, and align research focuses with the Amazon's strategic needs. We look for individuals who know how to deliver results and show a desire to develop themselves, their team, and their career. About the team Fulfillment Planning & Execution Science team contains a group of scientists with different technical backgrounds including Machine Learning and Operations Research, who will collaborate closely with you on your projects. Our team directly supports critical functional areas across Fulfillment Optimization and the research needs of the corresponding product and engineering teams. We tackle some of the most mathematically complex challenges in facility and transportation planning and execution to improve Amazon's operational efficiency worldwide and at a scale that is unique to Amazon. We often seek the opportunity of applying hybrid techniques in the space of Operations Research and Machine Learning to tackle some of our biggest technical challenges. We disambiguate complex supply chain problems and create ML and optimization solutions to solve those problems at scale.

As a Principal Scientist within the Artificial General Intelligence (AGI) organization, you are a trusted part of the technical leadership. You bring business and industry context to science and technology decisions. You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. You solicit differing views across the organization and are willing to change your mind as you learn more. Your artifacts are exemplary and often used as reference across organization. You are a hands-on scientific leader. Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems, acquiring expertise as needed. You decompose complex problems into straightforward solutions. You amplify your impact by leading scientific reviews within your organization or at your location. You scrutinize and review experimental design, modeling, verification and other research procedures. You probe assumptions, illuminate pitfalls, and foster shared understanding. You align teams toward coherent strategies. You educate, keeping the scientific community up to date on advanced techniques, state of the art approaches, the latest technologies, and trends. You help managers guide the career growth of other scientists by mentoring and play a significant role in hiring and developing scientists and leads. You will play a critical role in driving the development of Generative AI (GenAI) technologies that can handle Amazon-scale use cases and have a significant impact on our customers' experiences. Key job responsibilities You will be responsible for defining key research directions, adopting or inventing new machine learning techniques, conducting rigorous experiments, publishing results, and ensuring that research is translated into practice. You will develop long-term strategies, persuade teams to adopt those strategies, propose goals and deliver on them. You will also participate in organizational planning, hiring, mentorship and leadership development. You will be technically fearless and with a passion for building scalable science and engineering solutions. You will serve as a key scientific resource in full-cycle development (conception, design, implementation, testing to documentation, delivery, and maintenance). About the team The AGI team has a mission to push the envelope with multimodal LLMs and Gen AI in Computer Vision, in order to provide the best-possible experience for our customers.

The Artificial General Intelligence (AGI) team is looking for a highly skilled and experienced Senior Applied Scientist, to lead the development and implementation of cutting-edge algorithms and models for supervised fine-tuning and reinforcement learning through human feedback; with a focus across text, image, and video modalities. As a Senior Applied Scientist, you will play a critical role in driving the development of Generative AI (GenAI) technologies that can handle Amazon-scale use cases and have a significant impact on our customers' experiences. Key job responsibilities - Collaborate with cross-functional teams of engineers, product managers, and scientists to identify and solve complex problems in GenAI - Design and execute experiments to evaluate the performance of different algorithms and models, and iterate quickly to improve results - Think big about the arc of development of GenAI over a multi-year horizon, and identify new opportunities to apply these technologies to solve real-world problems - Communicate results and insights to both technical and non-technical audiences, including through presentations and written reports - Mentor and guide junior scientists and engineers, and contribute to the overall growth and development of the team

We are a part of Amazon Artificial General Intelligence (AGI) organization where our mission is “delight customers through contextual and personalized proactive experiences that keep customers informed, engaged, and productive without cognitive burden”. We are developing advanced systems 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 Senior Applied Scientist in the field of Natural Language Processing (NLP), Large Language Model (LLM), Recommender Systems and/or Information Retrieval, to invent and build scalable solutions for a state-of-the-art context-aware personal 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 a Senior Applied Scientist, you will leverage your technical expertise and experience to demonstrate leadership in tackling large complex problems, setting the direction and collaborating with applied scientists and engineers to develop novel algorithms and modeling techniques to enable timely, relevant and delightful recommendations and conversations. Your work will directly impact our customers in the form of products and services that make use of various machine learing, 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.

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.

Amazon.com’s Buyer Risk Prevention's (BRP) mission is to make Amazon the safest and most trusted place worldwide to transact online. BRP safeguards every financial transaction across all Amazon sites. As such, BRP designs and builds the software systems, risk models, and operational processes that minimize risk and maximize trust in Amazon.com. The BRP organization is looking for an Applied Scientist for the Buyer Abuse team, whose mission is to combine advanced analytics with investigator insight to create mechanisms to proactively and reactively reduce the impact of abuse across Amazon. Key job responsibilities As an Applied Scientist, you will be responsible for modeling complex problems, discovering insights, and building cutting edge risk algorithms that identify opportunities through statistical models, machine learning, and visualization techniques to improve operational efficiency and reduce monetary losses and improve customer trust. You will need to collaborate effectively with business and product leaders within BRP and cross-functional teams to build scalable solutions against high organizational standards. The candidate should be able to apply a breadth of tools, data sources, and ML techniques to answer a wide range of high-impact business questions and proactively present new insights in concise and effective manner. The candidate should be an effective communicator capable of independently driving issues to resolution and communicating insights to non-technical audiences. This is a high impact role with goals that directly impacts the bottom line of the business. Responsibilities: - Invent, implement, and deploy state of the art machine learning algorithms and systems - Build prototypes and explore conceptually new solutions - Define and conduct experiments to validate/reject hypotheses, and communicate insights and recommendations to Product and Tech teams - Take ownership of how ML solutions impact Amazon resources and Customer experience - Develop efficient data querying infrastructure for both offline and online use cases - Collaborate with cross-functional teams from multidisciplinary science, engineering and business backgrounds to enhance current automation processes - Learn and understand a broad range of Amazon’s data resources and know when, how, and which to use and which not to use. - Research and implement novel machine learning and statistical approaches - Maintain technical document and communicate results to diverse audiences with effective writing, visualizations, and presentations Please visit https://www.amazon.science for more information

We are looking for a leader of an R&D team in cutting-edge LLM technologies for applications across Alexa, AWS, and other Amazon businesses. In this role, you will innovate in the fastest-moving fields of current AI research, in particular in how to integrate a broad range of structured and unstructured information into AI systems (e.g. with RAG techniques), and get to immediately apply your results in highly visible Amazon products. If you are deeply familiar with LLMs, natural language processing, and machine learning and have experience managing high-performing research teams, this may be the right opportunity for you. Our fast-paced environment requires a high degree of independence in making decisions and driving ambitious research agendas all the way to production. You will work with other science and engineering teams as well as business stakeholders to maximize velocity and impact of your team's contributions. It's an exciting time to be a leader in AI research. In Amazon's AGI Information team, you can make your mark by improving information-driven experience of Amazon customers worldwide!

Amazon is investing heavily in building a world class advertising business and we are responsible for defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities. The ATT team, based in Bangalore, is responsible for ensuring that ads are relevant and are of good quality, leading to higher conversion for the sellers and providing a great experience for the customers. We deal with one of the world’s largest product catalog, handle billions of requests a day with plans to grow it by an order of magnitude and use automated systems to validate tens of millions of offers submitted by thousands of merchants in multiple countries and languages. We are searching for pioneers who are passionate about innovating and building state-of-the-art technologies for content understanding, labelling and generation in ads. In this role as an Applied Science Manager, you will drive a science charter and lead a team of applied scientists to develop novel scientific solutions to solve real-world problems for ads moderation and labelling, collaborate with cross functional leaders to define science strategies and lead your team to deliver product driven science solutions. This includes developing computer vision and machine learning models/methods (including but not limited to deep learning models, generative AI based models/solutions, large language models (LLMs) and vision language models (VLMs).

As a Senior Applied Scientist at Amazon, you will be at the forefront of a pioneering initiative to revolutionize customer experiences using Large Language Models (LLMs) and recommender systems. Your expertise will drive the personalization of every interaction across Amazon’s vast ecosystem, ensuring that each message and recommendation resonates personally with our customers. Your mission will be to harness the latest in LLM and machine learning innovations to craft recommender systems that are not just smart, but seem intuitively human. This is more than a technical role—it’s a chance to shape the future of e-commerce by making every user feel like Amazon’s most important customer. If you’re a visionary in the field of applied science, passionate about leveraging LLMs to create impactful, individualized user experiences, we want you. Help us set a new standard for personalization at Amazon, where every interaction is a step towards a more personalized future. Key job responsibilities - 3+ years of building machine learning models for business application experience - PhD, or Master's degree and 4+ years of applied research experience - Experience programming in Java, C++, Python or related language - Experience with neural deep learning methods and machine learning A day in the life You are an Applied Scientist with an interest in machine learning, data science, search, or recommendation systems. You have great problem solving skills. You love keeping abreast of the latest technology and use it to help you innovate. You have strong leadership qualities, great judgment, clear communication skills, and a track record of delivering great products. You enjoy working hard, having fun, and making history! About the team Our team has the autonomy to decide where we can have the most impact and get down to experimenting. We love metrics and the fast pace. We analyze data to uncover potential opportunities, generate hypotheses, and test them. We refuse to accept constraints, internal or external, and have a strong bias for action. We imagine, build prototypes, validate ideas, and launch follow-up experiments from the successful ones.

This role is target to working on MLSys and compilers for AWS Trainium in the open source domain. About the team Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred 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. 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. 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 and 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.