Member of Technical Staff, Research Engineering
Core
Design and scale Reinforcement Learning (RL) environments, training pipelines, and evaluation systems to advance AI model capabilities.
Role type
Senior IC Research Engineer (Reinforcement Learning)
Builds
Scalable RL training pipelines, automated data generation systems, and benchmarking frameworks.
Domain
Artificial Intelligence / Reinforcement Learning
Deliverable
production ML models
Required skills
Reinforcement Learning, environment design, training pipeline architecture, synthetic data generation, automated evaluation systems, open-source model fine-tuning, benchmarking frameworks
Preferred skills
Research publication experience, familiarity with evaluation ecosystems, scalable infrastructure for large-scale experimentation
Technologies
Reinforcement Learning frameworks, synthetic data tools, model validation libraries
Responsibilities
Architect self-contained RL environments with complex reward functions and verifiers; Design and scale episode pipelines and multi-component training processes; Build automated data generation systems leveraging synthetic data; Develop AI-driven evaluation and quality assurance systems; Fine-tune and optimize open-source RL models; Establish benchmarking frameworks to measure model capability and robustness.
