Founding Reinforcement Learning Engineer

Qualifications

• 2+ years of hands-on experience in reinforcement learning or machine learning engineering, with flexibility for more experienced candidates.
• Strong Python skills with deep experience in PyTorch or JAX.
• Practical experience in training models using reinforcement learning techniques, including policy gradient methods and RLHF.
• Familiarity with distributed training and GPU infrastructure, including tools like Ray, CUDA, and Kubernetes.
• Experience with LLM post-training or agent training is a plus, along with knowledge of Gymnasium, Ray RLlib, and similar frameworks.
• A degree in computer science, mathematics, physics, or a related field; advanced degrees are preferred.
• A proactive builder who thrives in a fast-paced, early-stage environment.

Responsibilities

• Design and build reinforcement learning environments, reward functions, and training pipelines.
• Train and fine-tune models using advanced reinforcement learning methods.
• Develop evaluation frameworks to assess model and agent performance.
• Run experiments, analyze results, and determine future exploration paths.
• Scale training processes on GPU clusters and ensure pipeline reliability.
• Transform research concepts into production-ready systems.
• Contribute to establishing the engineering culture and assist in hiring future engineers.

Benefits

• Opportunity to work directly with founders and influence technical direction.
• Engagement in a dynamic, early-stage AI team environment.
• Potential for significant impact on the company's growth and engineering culture.