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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 in training, fine-tuning, or optimizing models in PyTorch or JAX
  • Deep knowledge in one of the following: LLMs, GPU inference and performance, Reinforcement learning (RL), or Scientific ML
  • Ability to explain the complexity of problems for frontier models

Responsibilities

  • Develop innovative plans for challenging machine learning engineering tasks in a long-horizon AI research project
  • Design tasks that challenge frontier models, ensuring solutions in no more than 2 out of 8 attempts
  • Focus on inference, evaluation, and systems work over heavy model training. Balance tasks between GPU and CPU
  • Clearly articulate the complexity of problems for frontier models

Key facts

Hard skills

Other skills

  • Communication
  • Problem Solving

About the company

Mercor logo

Mercor

  • Job Boards & Talent Marketplaces
  • 51–200
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.

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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 innovative plans for challenging machine learning engineering tasks in a long-horizon AI research project.
  • Design tasks that challenge frontier models, ensuring solutions in no more than 2 out of 8 attempts.
  • Focus on inference, evaluation, and systems work over heavy model training. Balance tasks between GPU and CPU.
  • Clearly articulate the complexity of problems for frontier models.
  • Contribute ideas without the need to build or review tasks personally.

Qualifications

Must-Have

  • Current or recent role as an ML research engineer, research scientist, or applied scientist.
  • Experience in training, fine-tuning, or optimizing models in PyTorch or JAX.
  • Deep knowledge in one of the following: LLMs, GPU inference and performance, Reinforcement learning (RL), or Scientific ML.
  • Ability to explain the complexity of problems for frontier models.

Preferred

  • Experience writing benchmarks 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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