Tech Stack

Description

As a Research Engineer on the Reinforcement Learning team, you will collaborate with researchers and engineers to advance the capabilities and safety of large language models. You'll blend research and engineering, implementing novel approaches and contributing to the research direction, working on fundamental RL research and developing agentic models for tasks like computer use and autonomous software generation.

Requirements

• Proficient in Python and async/concurrent programming with frameworks like Trio
• Experience with machine learning frameworks (PyTorch, TensorFlow, JAX)
• Industry experience in machine learning research
• Strong systems design and communication skills
• Passionate about AI safety and beneficial systems

Responsibilities

• Architect and optimize core reinforcement learning infrastructure
• Design, implement, and test novel training environments, evaluations, and methodologies for RL agents
• Drive performance improvements through profiling, optimization, and benchmarking
• Implement efficient caching solutions and debug distributed systems
• Develop automated testing frameworks, design clean APIs, and build scalable infrastructure