Machine Learning Engineer

Mercor, backed by Benchmark and General Catalyst, is building a talent engine to move AI forward. We are looking for an Early-Career Machine Learning Engineer or ML PhD to tackle diverse problems in model benchmarking and performance improvement. This is a fully remote, asynchronous role designed for those who thrive on clear structure and measurable outcomes.

Key Responsibilities:

• ML Implementation: Draft detailed natural-language plans and code implementations for machine learning tasks.
• RL Environments: Convert novel machine learning problems into agent-executable tasks for reinforcement learning environments.
• Model Improvement: Identify failure modes and apply golden patches to LLM-generated trajectories to improve model performance.

Requirements:

• Experience: 0–2 years as a Machine Learning Engineer OR a PhD in Computer Science (with ML coursework).
• Tech Stack: Strong proficiency in Python and ML libraries like XGBoost, TensorFlow, and scikit-learn.
• Location: You MUST be currently based in the United States.
• Visa Status: We are unable to support H1-B or STEM OPT candidates. This is strictly for independent contractors authorized to work in the US.

Work Details & Benefits:

• Pay Rate: $80 - $120 per hour, depending on region and experience.
• Flexibility: Fully remote and asynchronous work schedule.
• Duration: Project runs through December 22nd, with potential extension into 2026.