About the RoleWe're looking for a
Research Engineer to join a small, fast-moving team building infrastructure for reinforcement learning environments and AI evaluation. You'll work at the intersection of applied research and engineering, helping develop and validate the systems that train and align AI models to real-world tasks. This role has direct impact on the quality and scalability of our core platform.
What You'll Do- Design, implement, and evaluate machine learning models and algorithms for RL-focused research problems.
- Build and maintain high-quality, reproducible research code across experimentation pipelines.
- Process and analyze datasets using standard scientific computing and data libraries.
- Run statistical analyses and design experiments to validate research hypotheses.
- Implement and reproduce methods from published research literature as needed.
- Use cloud computing platforms to scale research workloads and experiments.
- Create visualizations and communicate results clearly to technical teammates.
What We're Looking For- 3+ years of experience in research engineering, machine learning engineering, or applied research roles.
- Strong proficiency in Python for research implementation and experimentation.
- Hands-on experience designing and evaluating ML models or algorithms.
- Familiarity with deep learning frameworks such as PyTorch or TensorFlow.
- Experience with data processing and analysis libraries (e.g. NumPy, Pandas, Scikit-learn).
- Solid version control practices using Git for research codebases.
- Background in statistical analysis and experimental design.
- Experience with cloud platforms (AWS, GCP, or Azure) for compute-intensive workloads is a plus.
- Prior work implementing or reproducing research papers is a plus.
Compensation & BenefitsSalary range:
$150,000 - $250,000 USD annually. Visa sponsorship is not available at this time.
LocationThis role is on-site in
San Francisco, CA, USA.
