ML Research Engineer - AI Trainer

Role Description

Mercor connects elite creative and technical talent with leading AI research labs. The position is for a Human Baseliner for Open-Ended ML Research Tasks.

• 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

• 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.

Requirements

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

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

Resources & Support

• For details about the interview process and platform information, please check:
• For any help or support, reach out to: View email address on remotive.com
• Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.