DESCRIPTION
Our team is at the forefront of machine learning research. Led by scientists including Dean Foster, the team is dedicated to developing innovative RL algorithms and applying them to complex, real-world challenges in Amazon's global inventory and supply chain network. Our focus is not just on advancing theoretical knowledge but also on 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.
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 innovative solutions to complex business problems in collaboration with partner teams.
- Contribute to Amazon's global science community through collaboration and publication of ground-breaking 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 a part of our team, you will be working alongside thought leaders like 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 Reinforcement Learning, contributing both to the theoretical aspect of the field and its practical applications. We value innovative thinking and the ability to approach problems from new perspectives.
BASIC QUALIFICATIONS
- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning
PREFERRED QUALIFICATIONS
- 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 an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
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 https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.