Call For Referral is hiring: Machine Learning Software Engineer (Part-Time | $80
Call For Referral, San Francisco, CA, United States, 94199
Machine Learning Software Engineer (Part-Time | $80 –$120/hr)
Join to apply for the Machine Learning Software Engineer (Part-Time | $80 –$120/hr) role at Call For Referral.
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Base pay range: $80.00/hr - $120.00/hr
About the Role
At Mercor, we’re building the talent engine that helps leading labs and research organizations move AI forward. Our newest initiative focuses on benchmarking and improving model performance and training speed across real machine learning workloads.
If you’re an early-career Machine Learning Engineer or an ML-focused graduate student/PhD who values innovation, rigor, and meaningful impact, we’d love to meet you.
This is a remote, asynchronous, part-time opportunity ideal for individuals who thrive on clear structure and measurable outcomes.
What to Expect
- Schedule: Remote and asynchronous — set your own working hours
- Commitment: ~20 hours per 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 ML problems into agent-executable tasks for reinforcement learning environments
- Identify failure modes and apply golden patches to LLM-generated trajectories for ML tasks
What You’ll Bring
- Experience: 0–2 years as a Machine Learning Engineer or graduate-level experience in Computer Science, ML, or related coursework
- Required Skills: Familiarity with ML libraries: TensorFlow, XGBoost, scikit-learn, etc.; experience with model training, data preparation, and evaluation
- Bonus: Contributions to ML benchmarks or open-source ML tooling
Compensation & Terms
- Rate: $80–$120 per hour (based on experience and region)
- Payments: Weekly via Stripe Connect
How to Apply
- Complete the System Design Session (< 30 minutes)
- Fill out the Machine Learning Engineer Screen (< 5 minutes)
⚡ PS: Mercor reviews applications daily. Please complete your interview and onboarding steps to be considered for this opportunity. ⚡