Ml Research Engineer - Pytorch Expert

Mercor; San Francisco (CA); Hybrid; GBP 155,000 - 207,000; Full time

Job summary

Mercor is seeking a Machine Learning Expert for a remote contract role. The position focuses on advancing AI research tasks, evaluating frontier models, and optimizing inference and systems work across GPU/CPU resources.

Ideal candidates have a strong ML research background (PhD or MSc with publications) and hands-on experience with PyTorch or JAX, RL, LLMs, or Scientific ML. Prior Mercor contracts with strong performance are a plus.

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 LLMs, GPU inference and performance, RL, or Scientific ML.

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.

Skills

ML research engineer

research scientist

applied scientist

PyTorch

JAX

LLMs

GPU inference

Reinforcement learning

Scientific ML

Education

PhD in ML/CS/physics

MSc with strong research output

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.

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: [e-mail]