2027 Applied Science Internship - Reinforcement Learning & Optimization (Machine Learning) - United States, PhD Student Science Recruiting

What you'll do

• Develop and implement scalable algorithms and modeling techniques at the intersection of reinforcement learning and optimization.
• Build and evaluate machine learning models and automated processes for data analysis, validation, and implementation.
• Research and apply current machine learning techniques, using AI-powered tools where applicable and validating their outputs.

What they ask for

• Be enrolled in a PhD program.
• Be able to relocate to the internship location and work full-time (40 hours per week) for the entire internship.
• Have programming experience in Java and Python with PyTorch or JAX.
• Have experience in at least one listed area, such as optimization, statistics, reinforcement learning, causal inference, or deep learning, and demonstrated research depth through publications, thesis work, or equivalent contributions.

Nice to have

• Publications in top-tier peer-reviewed conferences or journals.
• Experience with deep learning model design, training, optimization, or pruning; modern RL toolkits; or AI-assisted development tools.

Pay

135,660.00 USD annually (base salary)

Tools

Java, Python, PyTorch, JAX, Stable Baselines, RLlib

AI focus

Research and develop reinforcement learning and optimization methods for machine learning; use and critically validate AI-powered tools to accelerate research, experimentation, and prototyping.