Machine Learning Engineer (Train AI Models Part Time!)
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. What to Expect 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.
- Schedule: Remote and asynchronous—set your own hours
- Commitment: ~20 hours/week
- Duration: Through December 22nd, with potential extension into 2026
What You’ll Do
- 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
What You’ll Bring
- 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
Compensation & Terms
- Rate: $80-$120/hr, depending on region and experience
- Payments: Weekly via Stripe Connect
- Engagement: Independent contractor
How to Apply
- Submit your resume
- Complete the System Design Session (Apply To This Job