Amazon
Sr. Applied Scientist - LLM/NLP, Private Brands Discovery
Amazon, Seattle, Washington, us, 98127
Sr. Applied Scientist - LLM/NLP, Private Brands Discovery
The Private Brands Discovery team designs innovative machine learning solutions to drive customer awareness for Amazon’s own brands and help customers discover products they love. This interdisciplinary team of Scientists and Engineers incubates and builds disruptive solutions using cutting-edge technology to solve some of the toughest science problems at Amazon. The team employs methods from Natural Language Processing, Deep Learning, multi-armed bandits, reinforcement learning, Bayesian Optimization, causal and statistical inference, and econometrics to drive discovery across the customer journey. Our solutions are crucial for the success of Amazon’s own brands and serve as a beacon for discovery solutions across Amazon.This is a high visibility opportunity for someone who wants to have business impact, dive deep into large-scale problems, enable measurable actions on the consumer economy, and work closely with scientists and engineers. As a scientist, 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. 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. With a focus on bias for action, this individual will be able to work equally well with Science, Engineering, Economics, and business teams.Key Responsibilities
Drive applied science projects in machine learning end-to-end: from ideation over prototyping to launch.Propose viable ideas to advance models and algorithms, with supporting argument, experiment, and preliminary results.Invent ways to overcome technical limitations and enable new forms of analyses to drive key technical and business decisions.Present results, reports, and data insights to both technical and business leadership.Constructively critique peer research and mentor junior scientists and engineers.Innovate and contribute to Amazon’s science community and external research communities.Minimum Qualifications
8+ years of building machine learning models for business application experience.4+ years of applied research experience.PhD, or Master's degree and 5+ years of applied research experience.Experience programming in Java, C++, Python or related language.Experience with neural deep learning methods and machine learning.Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.Experience with large scale distributed systems such as Hadoop, Spark etc.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. For individuals with disabilities who would like to request an accommodation, please visit
Amazon Disability Accommodation .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. For more information, please visit
Amazon Employee Benefits .This position will remain posted until filled. Applicants should apply via our internal or external career site.
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The Private Brands Discovery team designs innovative machine learning solutions to drive customer awareness for Amazon’s own brands and help customers discover products they love. This interdisciplinary team of Scientists and Engineers incubates and builds disruptive solutions using cutting-edge technology to solve some of the toughest science problems at Amazon. The team employs methods from Natural Language Processing, Deep Learning, multi-armed bandits, reinforcement learning, Bayesian Optimization, causal and statistical inference, and econometrics to drive discovery across the customer journey. Our solutions are crucial for the success of Amazon’s own brands and serve as a beacon for discovery solutions across Amazon.This is a high visibility opportunity for someone who wants to have business impact, dive deep into large-scale problems, enable measurable actions on the consumer economy, and work closely with scientists and engineers. As a scientist, 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. 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. With a focus on bias for action, this individual will be able to work equally well with Science, Engineering, Economics, and business teams.Key Responsibilities
Drive applied science projects in machine learning end-to-end: from ideation over prototyping to launch.Propose viable ideas to advance models and algorithms, with supporting argument, experiment, and preliminary results.Invent ways to overcome technical limitations and enable new forms of analyses to drive key technical and business decisions.Present results, reports, and data insights to both technical and business leadership.Constructively critique peer research and mentor junior scientists and engineers.Innovate and contribute to Amazon’s science community and external research communities.Minimum Qualifications
8+ years of building machine learning models for business application experience.4+ years of applied research experience.PhD, or Master's degree and 5+ years of applied research experience.Experience programming in Java, C++, Python or related language.Experience with neural deep learning methods and machine learning.Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.Experience with large scale distributed systems such as Hadoop, Spark etc.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. For individuals with disabilities who would like to request an accommodation, please visit
Amazon Disability Accommodation .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. For more information, please visit
Amazon Employee Benefits .This position will remain posted until filled. Applicants should apply via our internal or external career site.
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