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ML Research Engineer - PyTorch Expert

Role overview

Qualifications

  • Current or recent role as an ML research engineer, research scientist, or applied scientist
  • Experience with training, fine-tuning, or optimizing models in PyTorch or JAX
  • Deep knowledge in at least one area: LLMs, GPU inference and performance, Reinforcement learning (RL), or Scientific ML
  • Ability to explain why a problem is hard for a frontier model

Responsibilities

  • Develop challenging machine learning engineering tasks for a long-horizon AI research project
  • Design tasks that challenge frontier models, ensuring they are solved in no more than 2 out of 8 attempts
  • Focus on inference, evaluation, and systems work rather than heavy model training
  • Clearly explain why each problem is difficult for a frontier model

Key facts

Hard skills

Other skills

  • Communication
  • Problem Solving

About the company

Mercor logo

Mercor

Job Boards & Talent Marketplaces

Our vast talent network trains frontier AI models in the same way teachers teach students: by sharing knowledge, experience, and context that can't be captured in code alone. Today, more than 30,000 experts in our network collectively earn over $2 million a day.

Company details

IndustryJob Boards & Talent Marketplaces
Company size51 - 200

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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: Machine Learning Expert
Type: Contract
Compensation: $150–$200/hour
Location: Remote

Role Responsibilities

  • Develop challenging machine learning engineering tasks for a long-horizon AI research project.
  • Design tasks that challenge frontier models, ensuring they are solved in no more than 2 out of 8 attempts.
  • Focus on inference, evaluation, and systems work rather than heavy model training. Tasks run on both GPU and CPU.
  • Clearly explain why each problem is difficult for a frontier model.
  • Contribute ideas without needing to build or review the tasks yourself.

Qualifications

Must-Have

  • Current or recent role as an ML research engineer, research scientist, or applied scientist.
  • Experience with training, fine-tuning, or optimizing models in PyTorch or JAX.
  • Deep knowledge in at least one area: LLMs, GPU inference and performance, Reinforcement learning (RL), or Scientific ML.
  • Ability to explain why a problem is hard for a frontier model.

Preferred

  • Experience writing benchmark or evaluation questions.
  • PhD in ML, CS, or physics, or an MSc with strong research output.
  • Publications.
  • Prior Mercor contracts with strong performance.

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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Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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