Principal Applied Scientist, Amazon Private Brands

2 weeks ago

Seattle, United States Amazon.com Services LLC Full time $179,000 - $309,400
  • 10+ years minimum of hands-on science application experience
  • PhD in a relevant technical field (or equivalent experience in some cases)
  • Strong publication track record
The Amazon Private Brands’ Discovery team develops innovative machine learning solutions to enhance customer awareness of Amazon's private brands and help customers discover products they love. This interdisciplinary team of scientists and engineers incubates and builds disruptive technologies, tackling some of the most complex scientific challenges at Amazon. To achieve this, we leverage a wide range of advanced techniques, including Natural Language Processing (NLP), deep learning, large language models (LLMs), multi-armed bandits, reinforcement learning, Bayesian optimization, causal and statistical inference, and econometrics, to drive discovery throughout the customer journey. Our solutions are not only critical to the success of Amazon's private brands but also serve as a leading example of discovery technologies across Amazon.

We are seeking a Principal Scientist to join our team and lead the development of cutting-edge machine learning models and algorithms that will drive innovative discovery solutions for Amazon Private Brands. In this hands-on role, you will apply your expertise to propose solutions, create software prototypes, and successfully transition these prototypes into production systems using modern software development tools and methodologies. You will also be responsible for scaling these solutions to meet the growing and evolving needs of our customers. As a Principal Scientist, you will play a pivotal role in shaping the vision, design, and roadmap for complex, previously unsolved problems, guiding solutions from inception to implementation. Strong verbal and written communication skills, a self-driven mindset, and the ability to deliver high-quality results in a fast-paced environment are essential for success in this role.

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 have 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).

  • Experience programming in Java, C++, Python or related language]
  • Experience in building ML systems for online advertising
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 https://www.amazon.jobs/en/disability/us.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $179,000/year in our lowest geographic market up to $309,400/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 https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.

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