2026 Fall Applied Science Internship - Reinforcement Learning & Optimization (Machine Learning) - United States, PhD Student Science Recruiting

Key job responsibilities

We are particularly interested in candidates with expertise in: Optimization, Programming/Scripting Languages, Statistics, Reinforcement Learning, Causal Inference, Large Language Models, Time Series, Graph Modeling, Supervised/Unsupervised Learning, Deep Learning, Predictive Modeling

Basic Qualifications

• Are enrolled in a PhD
• Can relocate to where the internship is based
• Experience programming in Java, C++, Python or related language
• Experience with one or more of the following: Optimization, Programming/Scripting Languages, Statistics, Reinforcement Learning, Causal Inference, Large Language Models, Time Series, Graph Modeling, Supervised/Unsupervised Learning, Deep Learning, Predictive Modeling
• Must be available for full-time (40 hours per week) internship for the whole duration of the internship

Preferred Qualifications

• Have publications at top-tier peer-reviewed conferences or journals
• Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning

Pay

The starting pay for this position is listed below. Final starting pay will be based on factors including experience, qualifications, and location.

• USA, OR, Corvallis - 142,800.00 - 193,200.00 USD annually
• USA, WA, SEATTLE - 142,800.00 - 193,200.00 USD annually
• USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually