Research Engineer

Job Summary

Focused on developing reinforcement learning capabilities, the hybrid Research Engineer position will design benchmarks and evaluation methodologies, write production code, and collaborate with cross-functional teams to enhance model evaluation for enterprise clients.

Key responsibilities

• Design benchmarks and reinforcement learning environments to assess model capabilities
• Originate evaluation methodologies and create scoring frameworks and evaluation architectures
• Write and ship production code while building and maintaining data pipelines for evaluation runs

Required qualifications

• Fluency in Python and experience with the modern machine learning stack
• Real experience in building evaluation systems, reinforcement learning environments, or training and inference infrastructure
• Hands-on experience with modern agentic flows
• Familiarity with reinforcement learning methods and frontier model evaluations
• A proven track record of turning ambiguous research questions into functional systems