RL Environment Engineer (ML Engineer)
Requirements • Master’s degree in Computer Science, AI, ML, or a related technical field, • (Desirable) Deep knowledge of transformer internals or LLM training/inference, • Strong Python skills with production-quality engineering standards, • (Desirable) Experience with inference libraries such as vLLM or SGLang, • Experience designing or working with RL environments or training pipelines, • (Desirable) CUDA or custom kernel optimization experience (e.g. Pallas), • Solid understanding of modern LLMs and their limitations, • (Desirable) Research experience with publications or high-quality open-source work, • Ability to work quickly, iterate reliably, and respond to feedback, • (Desirable) Experience building complex or open-ended RL-based learning systems, • Advanced English proficiency (C1/C2) What the job involves • Design and build reinforcement learning environments for training and evaluating LLMs, • Translate modern ML and AI research into structured RL problems, • Implement reliable, debuggable, and scalable training environments in Python, • Collaborate with researchers and engineers to improve model learning quality, • Complete an average of two well-scoped tasks per week, • Iterate quickly based on feedback and evaluation results Apply tot his job