In this role you'll have the opportunity to make meaningful advancements in machine learning and AI, contributing to both theoretical and applied aspects of ML and RL.
Key job responsibilities
- Design, implement, and evaluate innovative models, agents, and software prototypes.
- Collaborate with a team of experienced scientists to drive technological advancements.
- Develop novel solutions to complex business problems in collaboration with partner teams.
- Contribute to Amazon's global science community through collaboration and publication of groundbreaking research.
- Engage in research projects that contribute to the wider scientific community, sharing findings through publications in top-tier journals and conferences.
A day in the life
As part of our team, you will work alongside thought leaders like Sham Kakade and Dean Foster, contributing to academic research and complex, real-world applications. Your work will directly influence Amazon's global inventory planning systems, shaping decisions that affect billions of dollars worth of inventory and a wide array of product lines.
You will tackle complex inventory planning challenges using RL, contributing both to the theoretical aspect of the field and its practical applications. We value creative thinking and the ability to approach problems from new perspectives.
About the team
Our team is at the forefront of machine learning research; we are dedicated to developing novel RL algorithms and applying them to complex, real-world challenges in Amazon's global inventory and supply chain network. Our focus is on both advancing theoretical knowledge and implementing these insights to optimize operations and enhance customer satisfaction.
We foster a collaborative environment where exploration of new ideas and tackling complex problems is encouraged. The supply chain spans a wide range of operations, managing decisions that impact billions of dollars worth of inventory. For scientists passionate about impactful research in machine learning and AI, our team offers a dynamic and fulfilling environment to make a tangible difference in the field and Amazon's operations.
BASIC QUALIFICATIONS
- PhD, or Master's degree and 4+ years of quantitative field research experience
- Experience investigating the feasibility of applying scientific principles and concepts to business problems and products
- 2+ years of building machine learning models for business application experience
- Experience programming in Java, C++, Python or related language
- Solid track record of research, demonstrated by publication in peer-reviewed conferences or journals, focusing on reinforcement learning, deep learning, and machine learning
- Experience in algorithm development
- Proficiency in Python or similar, including experience with machine learning frameworks
PREFERRED QUALIFICATIONS
- Expertise in Reinforcement Learning or Machine Learning.
- Familiarity with the latest trends in Machine Learning.
- Track record of developing novel algorithms and advancing the state of the art.
- 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!
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 $136,000/year in our lowest geographic market up to $212,800/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.