Research Engineer (Reinforcement Learning)

📋 Description

• Build training environments, verifiers, and supporting infrastructure for post-training models.
• Own the synthetic data pipeline from data generation through quality assurance and validation.
• Run end-to-end training experiments, analyze results, and identify factors driving model
• Design and maintain evaluations that models must pass before production releases.
• Select and adapt open-weight foundation models for agent and product needs.
• Develop trained behaviors for voice and text-based agents.

🎯 Requirements

• Strong Python engineering skills and ability to build production-quality systems.
• Experience taking an ML model from raw data through experimentation to production.
• Data-centric mindset: coverage, diversity, quality, and data leakage awareness.
• Ability to design robust rewards, verifiers, and evaluation mechanisms to avoid reward exploitation.
• Practical experience with GPUs and understanding their capabilities/limitations.
• Judgment on when training is the right solution vs simpler approaches.

🎁 Benefits

• Opportunity to impact a fast-growing developer platform.
• Small, senior engineering team with emphasis on technical excellence, creativity, ownership.
• Competitive salary and equity package.
• Health, dental, and vision benefits.
• Flexible vacation policy.
• Remote-friendly environment with autonomy.