Remote Machine Learning Engineer - AI Trainer

Overview

At Mercor, we’re building the talent engine that helps leading labs and research orgs move AI forward. Our latest initiative focuses on benchmarking and improving model performance and training speed across real ML workloads. If you’re an early-career Machine Learning Engineer or an ML PhD who cares about innovation and impact, we’d love to meet you.

As a Machine Learning Engineer, you’ll tackle diverse problems that explore ML from unconventional angles. This is a remote, asynchronous, part-time role designed for people who thrive on clear structure and measurable outcomes.

• Commitment: ~20 hours / week
• Duration:
  Through December 22nd, with potential extension into 2026

• 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

• Experience:
  
  0–2 years as a Machine Learning Engineer or a PhD in Computer Science (Machine Learning coursework required)
• Required Skills:
  
  Python, ML libraries (XGBoost, Tensorflow, scikit-learn, etc.), data prep, model training, etc.
• Bonus:
  Contributor to ML benchmarks
• Location:
  
  MUST be based in the United States

• Rate: $80-$120 / hr, depending on region and experience

Mercor is a talent marketplace connecting top experts with leading AI labs and research organizations. Our investors include Benchmark, General Catalyst, Adam D’Angelo, Larry Summers, and Jack Dorsey. Thousands of professionals across law, creative fields, engineering, and research use Mercor to work on frontier projects shaping the next era of AI.