Amazon
Sr. Applied Scientist , AFT AI, Amazon Fulfillment Technologies (AFT)
Amazon, Bellevue, Washington, us, 98009
Job ID: 2773282 | Amazon.com Services LLCAre you excited about developing cutting-edge generative AI, large language models (LLMs), and foundation models? Are you looking for opportunities to build and deploy them on real-world problems at a truly vast scale with global impact? At AFT (Amazon Fulfillment Technologies) AI, a group of around 50 scientists and engineers, we are on a mission to build a new generation of dynamic end-to-end prediction models (and agents) for our warehouses based on GenAI and LLMs. These models will be able to understand and make use of petabytes of human-centered as well as process information, and learn to perceive and act to further improve our world-class customer experience – at Amazon scale.We are looking for a Sr. Applied Scientist who will become one of the research leads in a team that builds next-level end-to-end process predictions and shift simulations for all systems in a full warehouse with the help of generative AI, graph neural networks, and LLMs. Together, we will be pushing beyond the state of the art in simulation and optimization of one of the most complex systems in the world: Amazon's Fulfillment Network.Key job responsibilities
In this role, you will dive deep into our fulfillment network, understand complex processes, and channel your insights to build large-scale machine learning models (LLMs and Transformer-based GNNs) that will be able to understand (and, eventually, optimize) the state and future of our buildings, network, and orders.You will face a high level of research ambiguity and problems that require creative, ambitious, and inventive solutions. You will work with and in a team of applied scientists to solve cutting-edge problems going beyond the published state of the art that will drive transformative change on a truly global scale.You will identify promising research directions, define parts of our research agenda and be a mentor to members of our team and beyond. You will influence the broader Amazon science community and communicate with technical, scientific and business leaders.If you thrive in a dynamic environment and are passionate about pushing the boundaries of generative AI, LLMs, and optimization systems, we want to hear from you.BASIC QUALIFICATIONS
3+ years of building machine learning models for business application experiencePhD, or Master's degree and 6+ years of applied research experienceExperience programming in Java, C++, Python or related languageExperience with Large Language ModelsPREFERRED QUALIFICATIONS
You have been the lead scientist on a team that has put a non-obvious/non-trivial deep learning system into productionStrong publication record on LLMs/NLP or Graph Neural NetsExpertise with complex multivariate time series prediction (ideally with transformers)Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
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In this role, you will dive deep into our fulfillment network, understand complex processes, and channel your insights to build large-scale machine learning models (LLMs and Transformer-based GNNs) that will be able to understand (and, eventually, optimize) the state and future of our buildings, network, and orders.You will face a high level of research ambiguity and problems that require creative, ambitious, and inventive solutions. You will work with and in a team of applied scientists to solve cutting-edge problems going beyond the published state of the art that will drive transformative change on a truly global scale.You will identify promising research directions, define parts of our research agenda and be a mentor to members of our team and beyond. You will influence the broader Amazon science community and communicate with technical, scientific and business leaders.If you thrive in a dynamic environment and are passionate about pushing the boundaries of generative AI, LLMs, and optimization systems, we want to hear from you.BASIC QUALIFICATIONS
3+ years of building machine learning models for business application experiencePhD, or Master's degree and 6+ years of applied research experienceExperience programming in Java, C++, Python or related languageExperience with Large Language ModelsPREFERRED QUALIFICATIONS
You have been the lead scientist on a team that has put a non-obvious/non-trivial deep learning system into productionStrong publication record on LLMs/NLP or Graph Neural NetsExpertise with complex multivariate time series prediction (ideally with transformers)Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
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