Remote ML Research Engineer - Open-Ended Tasks

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

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.