Research Engineer, Reinforcement Learning

Job description

Research Engineer – Reinforcement Learning Location: San Francisco (Hybrid) About TensorStax TensorStax is building fully autonomous AI systems to manage and maintain mission-critical data infrastructure and pipelines. We leverage reinforcement learning to enhance language models' ability to reason over large-scale data lakes and warehouses, detect pipeline failures, construct new pipelines with high precision, and enable agentic behavior—allowing systems to proactively identify and resolve issues autonomously. As a Research Engineer specializing in Reinforcement Learning, you will: - Develop and refine reward functions to optimize agent behavior for complex data engineering tasks. - Create RL gym environments for language model agents. - Fine-tune language models using reinforcement learning techniques such as PPO, DPO, and KTO. - Stay at the forefront of research on RL for language models, incorporating advancements like GRPO, SWE-Gym, and SWE-RL into practical applications. - Curate and build high-quality datasets for supervised fine-tuning (SFT) and RLHF. - Design experiments to evaluate and improve the agentic capabilities of language models in data environments. What We’re Lo...