This role is with Mercor. Mercor uses RippleMatch to find top talent.
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.
Schedule: Remote and asynchronous—set your own hours
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
Payments: Weekly via Stripe Connect
Engagement: Independent contractor
Submit your resume on Mercor's website
Complete the System Design Session (< 30 minutes)
Fill out the Machine Learning Engineer Screen (<5 minutes)
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Understand the required skills and qualifications, anticipate the questions you may be asked, and study well-prepared answers using our sample responses.
Machine Learning Engineer Q&A's