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ML Engineer - Model Evaluation

Role overview

Qualifications

  • MSc or PhD in machine learning, computer science, or a related STEM field
  • 1+ years of experience in a research or research-engineering role
  • Experience in training and evaluating ML models and running experiments end-to-end
  • Strong familiarity with large language models and their evaluation techniques

Responsibilities

  • Design tasks by turning real ML research ideas into well-defined, multi-step tasks
  • Run experiments by implementing changes, running training experiments, and analyzing results
  • Explore reinforcement learning ideas, focusing on reward functions and training behavior
  • Evaluate models to identify where frontier models fall short

Key facts

Hard skills

About the company

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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 Engineer — Model Evaluation & Experimentation
Type: Contract
Compensation: $60–$90/hour
Location: Remote
Commitment: 35 hours/week

Role Responsibilities

  • Design tasks by turning real ML research ideas into well-defined, multi-step tasks.
  • Run experiments by implementing changes, running training experiments, and analyzing results.
  • Explore reinforcement learning ideas, focusing on reward functions and training behavior.
  • Evaluate models to identify where frontier models fall short.
  • Collaborate with researchers and experts to maintain task consistency and rigor.

Qualifications

Must-Have

  • MSc or PhD in machine learning, computer science, or a related STEM field.
  • 1+ years of experience in a research or research-engineering role.
  • Experience in training and evaluating ML models and running experiments end-to-end.
  • Strong familiarity with large language models and their evaluation techniques.
  • Proficiency in Python and Git.

Preferred

  • Basic understanding of reinforcement learning.
  • Experience in AI training, model evaluation, or benchmark/task authoring.

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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