Research Engineer for Reinforcement Learning

This role focuses on advancing the capabilities of modern AI models through the development of innovative Reinforcement Learning (RL) environments, training pipelines, and evaluation systems. As a key member of the Research Engineering team, you will operate at the intersection of research and production, transforming experimental concepts into scalable, high-performance systems.

• Architect self-contained RL environments that capture complex, real-world tasks, including reward functions, verifiers, and evaluation logic.
• Design and scale episode pipelines and multi-component training processes (MCPs) to support reproducible experimentation.
• Build automated data generation systems, utilizing synthetic data to accelerate training cycles without compromising quality.
• Develop and integrate AI-driven evaluation and quality assurance systems for automated grading, validation, and feedback loops.
• Fine-tune and optimize open-source RL models using internally generated datasets and custom training strategies.
• Establish benchmarking frameworks to measure model capability, robustness, and data quality across tasks.
• Contribute to the release and analysis of evaluations on internal and external benchmark platforms.

• Deep experience in Reinforcement Learning, including environment design and training dynamics.
• Strong track record of building and scaling RL systems, pipelines, or experimentation frameworks.
• Proficient in automation and data generation, including synthetic data pipelines.
• Familiar with automated evaluation systems, model validation, and quality assurance workflows.
• Experienced in fine-tuning and evaluating open-source ML models.
• Clear, concise communicator with strong technical writing skills.
• Comfortable operating in fast-paced, research-driven, and highly collaborative environments.

This is a full-time, remote position.

The national pay range for this position is a base salary of $220, 000, $500, 000 USD, with eligibility for equity compensation and performance-based bonuses, subject to company policies.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, veteran status, or any other characteristic protected by applicable local laws and regulations.