Research Engineer

About this role

Join a fast-growing team to build infrastructure for reinforcement learning and AI evaluation systems. You'll design ML models, develop reproducible research code, and validate algorithms that train and align AI systems at scale.

What you'll do

• Design and implement ML models and algorithms for reinforcement learning research problems
• Build and maintain high-quality, reproducible research code for experimentation pipelines
• Process and analyze datasets using scientific computing libraries like NumPy and Pandas
• Design and run experiments with statistical validation to test research hypotheses
• Implement and reproduce methods from published research papers
• Scale research workloads using cloud computing platforms and create clear visualizations of results

What they're looking for

• Python for research and experimentation
• Machine learning model design and evaluation
• Deep learning frameworks (PyTorch or TensorFlow)
• Data processing libraries (NumPy, Pandas, Scikit-learn)
• Statistical analysis and experimental design
• Git version control
• Cloud platforms (AWS, GCP, or Azure)
• Research paper implementation and reproduction

Benefits

• Competitive salary ($150,000–$250,000 annually)
• Work on cutting-edge reinforcement learning infrastructure
• Direct impact on AI alignment and model training quality
• Collaborate with small, fast-moving technical team
• On-site location in San Francisco