Fall ML & RL Applied Science Internship

Amazon; Corvallis (OR); On-site; USD 143,000 - 193,000; Full time

Benefits offered by this job

EAP

Mental Health Support

Medical Advice Line

401(k) matching

Job summary

Amazon Science is seeking graduate student scientists to turn cutting-edge theory into impactful practice. You will conduct research in deep reinforcement learning, Bayesian optimization, time series, and ML modeling, collaborating with product managers, scientists, and engineers to deploy scalable algorithms on production data.

The role emphasizes exploration of supervised, semi-supervised, and unsupervised learning, with access to state-of-the-art infrastructure and mentorship, in a

Qualifications

• Enrolled in a PhD program.
• Willing to relocate to the internship location.
• Proficient in Java, C++, Python or related language.
• Experience in Optimization, RL, Time Series, Graph Modeling, DL, and Predictive Modeling.

Responsibilities

• Develop scalable ML models and algorithms for production-scale data analysis and modeling.
• Research and implement RL/Optimization techniques to advance state-of-the-art in ML.
• Collaborate with cross-functional teams of product managers, scientists, and software engineers.

Skills

Java

C++

Python

Optimization

Reinforcement Learning

Time Series

Graph Modeling

Deep Learning

Predictive Modeling

Large Language Models

Education

PhD

Job description

Amazon Science is seeking graduate student scientists to turn cutting-edge theory into impactful practice. You will conduct research in deep reinforcement learning, Bayesian optimization, time series, and ML modeling, collaborating with product managers, scientists, and engineers to deploy scalable algorithms on production data.

The role emphasizes exploration of supervised, semi-supervised, and unsupervised learning, with access to state-of-the-art infrastructure and mentorship, in a