Research Engineer (Reinforcement Learning)

📋 Description

• Build environments, verifiers, and infra for post-training models.
• Own synthetic data pipeline from generation to QA.
• Run end-to-end training experiments and analyze results.
• Design evaluations for production releases.
• Adapt open-weight foundation models for agents/products.
• Develop robust multi-turn agent behaviors (voice/text).

🎯 Requirements

• Strong Python engineering for production systems.
• Experience taking ML models from data to production.
• Data-centric mindset: coverage, quality, leakage awareness.
• Design robust rewards, verifiers, and eval mechanisms.
• GPU experience; understanding of their limits.
• Judgment on when to train vs simpler approaches.

🎁 Benefits

• Impact on a fast-growing developer platform.
• Small, experienced team with ownership.
• Competitive salary and equity.
• Health, dental, vision benefits.
• Flexible vacation policy.
• Remote-friendly environment with autonomy.