Reinforcement learning & optimization intern

Program structure
Track: Research engineering
Reports to: Staff research engineer, EOS Intelligence Plane team
Duration: 20–24 weeks, full-time preferred
Primary languages: Python (Py Torch or JAX), familiarity with Stable Baselines / Clean RL / Torch RL
Outcome: A trained, sim-validated routing policy that demonstrably improves utility- per-dollar over the production baseline
Compensation: stipend per internal scale; conversion to full-time considered for strong performers.
Mentorship: each intern is paired with a senior engineer or researcher who is the technical owner of the area.
How to apply: Send
• Resume / CV (PDF).
• A link to a Git Hub profile, portfolio, or representative project.
• The role number(s) you are applying for. You can apply for up to two.
• The application-prompt response for the role you are most interested in (300–500 words).
Applications without the prompt response will be deprioritized it is the single most useful signal...