Research Engineer, Reinforcement Learning
tensorstaxMillbrae (CA)
Research Engineer, Reinforcement Learning
Posted today
tensorstaxMillbrae (CA)
SENIORITY
Mid
About the role
Research Engineer – Reinforcement Learning
Location: San Francisco (Hybrid)
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 Looking For:
Deep understanding of reinforcement learning, reward shaping, and optimization strategies.
Strong familiarity with LLM fine-tuning techniques (PPO, DPO, KTO) and their applications in reinforcement learning.
Knowledge of recent advancements in RL for language models (GRPO, SWE-Gym, SWE-RL).Experience curating and constructing high-quality datasets for fine-tuning.
Strong problem-solving skills and a history of working on complex ML projects.
High agency—ability to work independently, experiment proactively, and drive research initiatives forward.
Bonus Points:
Experience with distributed training in PyTorch (DDP, FSDP).Hands-on experience designing RL environments for traditional RL problems.
Contributions to open-source projects in RL, LLMs, or ML infrastructure.
Familiarity with data lakes and warehouses (Snowflake, BigQuery, Redshift).
Benefits:
100% employer-covered health, dental, and vision insurance.401(k) with company match. Access to Bay Club or Equinox in San Francisco.
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