Summer 2027 AI Applied Research Internship

What you'll do

• Translate operational processes into tractable modeling problems; build simulations and models using reinforcement learning, optimization, or forecasting.
• Design reproducible experiments, evaluate results, and communicate findings to technical and non-technical stakeholders.
• Work with engineering on production deployment, monitoring, updates, and safe overrides of models.

What they ask for

• Currently pursuing an MS or PhD in a listed quantitative field or related field, returning to the program after the fellowship, with expected graduation December 2027 or later.
• Production-quality Python and PyTorch, with solid machine learning fundamentals.
• Hands-on experience with reinforcement learning, mathematical optimization, simulation and modeling, or time-series forecasting; ability to formulate messy real-world processes as tractable models.
• Demonstrated ability to design, implement, and evaluate experiments using reproducible research practices; able and willing to work on-site in Washington DC for the full program; U.S. Person status required.

Nice to have

• Deep RL, combinatorial optimization with ML, multi-agent RL, stochastic or robust optimization, uncertainty quantification, or game-theory/behavioral-science perspectives.
• MLOps or exposure to construction, infrastructure, energy, industrial control systems, or critical-infrastructure security.

Pay

USD $25.00 an hour (starting rate); USD $2,000 monthly housing stipend

Tools

Python, PyTorch, PPO, SAC, DQN, IQL, CQL, TD3+BC

AI focus

Applied AI research using reinforcement learning, optimization, forecasting, simulation, and anomaly detection to support operational decisions and production decision systems.