Machine Learning Expert - Fully Remote | Upto $90/hr

mercor; United States; Remote; USD 103,000 - 124,000; Part time

Job summary

Mercor is seeking a Human Baseliner for open-ended ML research tasks on a remote contract basis. Expect to work 20+ hours per week with compensation of $75–$90 per hour. Tasks are performed in a sandboxed Linux environment, with documentation and evaluation requirements.

The role requires 3+ years in ML and a top-tier university background or FAANG-equivalent experience, plus proficiency in PyTorch, JAX, or TensorFlow and deep expertise in a focal ML area.

Qualifications

• 3+ years of machine learning experience (PhD time counts).
• Attended a top-100 university or worked at FAANG or a comparable company.
• Experience with PyTorch, JAX, or TensorFlow.
• Deep expertise in at least one focus area: pretraining, PPO, reward shaping, fine-tuning, LoRA, RLHF, architecture design, contrastive training, generative modeling, multilingual experience, or data pipelines.

Responsibilities

• Attempt open-ended machine learning research tasks under a fixed time and compute budget.
• Work independently in a sandboxed Linux environment with internet access.
• Use preferred tools, including IDEs and AI coding assistants like Cursor, Claude Code, and ChatGPT.
• Record full working sessions via screen recording.
• Complete pre-task and post-task questionnaires.
• Submit final work product, screen recording, and completed questionnaires for evaluation.

Skills

3+ years ML experience

Top-tier university or FAANG exposure

Tools

PyTorch

JAX

TensorFlow

Job description

About the job

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark , General Catalyst , Peter Thiel , Adam D'Angelo , Larry Summers , and Jack Dorsey .

Position: Human Baseliner for Open-Ended ML Research Tasks

Type: Contract

Compensation: $75–$90/hour

Location: Remote

Commitment: 20+ hours/week

Role Responsibilities

• Attempt open-ended machine learning research tasks under a fixed time and compute budget.
• Work independently in a sandboxed Linux environment with internet access.
• Use preferred tools, including IDEs and AI coding assistants like Cursor , Claude Code , and ChatGPT .
• Record full working sessions via screen recording.
• Complete pre-task and post-task questionnaires.
• Submit final work product, screen recording, and completed questionnaires for evaluation.

Qualifications Must-Have

• 3+ years of machine learning experience . Time in a PhD program counts.
• Attended a top-100 university or worked at FAANG or a comparable company .
• Experience with PyTorch , JAX , or TensorFlow .
• Deep expertise in at least one focus area: pretraining, PPO , reward shaping, fine-tuning, LoRA , RLHF , architecture design, contrastive training, generative modeling, multilingual experience, or data pipelines.

Required Domain Expertise

• Practical experience in Pretraining , Reinforcement learning , Post-training , Dataset curation , or Model architecture .

Logistics

• One baseline attempt per contractor per task.
• Each task may only be attempted once.
• All work is confidential and covered by NDA.
• Compute and environment are provided; no personal GPU required.