Mercor is building a talent engine to help leading labs and research organizations advance AI, with a focus on benchmarking and improving model performance and training speed across real ML workloads.
Requirements
- 0–2 years as a Machine Learning Engineer or a PhD in Computer Science (Machine Learning coursework required)
- Python
- ML libraries (XGBoost, Tensorflow, scikit-learn, etc.)
- Data prep
- Model training
- Contributor to ML benchmarks
Responsibilities
- Draft detailed natural-language plans and code implementations for machine learning tasks
- Convert novel machine learning problems into agent-executable tasks for reinforcement learning environments
- Identify failure modes and apply golden patches to LLM-generated trajectories for machine learning tasks
Other
- MUST be based in the United States
- Remote and asynchronous—set your own hours
- ~20 hours/week commitment
- Duration: Through December 22nd, with potential extension into 2026
- Submit your resume on Mercor's website
