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ML Research Engineer - PhD - AI Trainer

Roles & Responsibilities

  • 3+ years of machine learning experience
  • 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

Requirements:

  • 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

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.

Application Process (Takes 20–30 mins to complete)

  • Upload resume
  • AI interview based on your resume
  • Submit form

Resources & Support

  • For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome
  • For any help or support, reach out to: support@mercor.com

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.



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