ML Engineer - Model Evaluation Expert

• Run experiments by implementing changes, executing training experiments, and analyzing results to define correct solutions.
• Explore reinforcement learning concepts such as reward functions and training behavior in task development.
• Evaluate frontier models’ performance on tasks and identify areas of improvement.
• Collaborate with researchers to ensure tasks are consistent, rigorous, and fair.

Must-Have

• MSc or PhD in machine learning, computer science, or a related STEM field.
• 1+ years in a research or research-engineering role.
• Experience in training and evaluating ML models and conducting end-to-end experiments.
• Proficiency in Python and Git.
• Strong understanding of large language models and their evaluation.

Preferred

• Basic knowledge of reinforcement learning.
• Experience in AI training, model evaluation, or benchmark/task authoring.

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D’Angelo, Larry Summers, and Jack Dorsey.