MLOps Engineer Expert

Mercor • United State
Remote
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AI Summary

Mercor is seeking an experienced MLOps Engineer Expert to guide research and engineering teams in improving AI model performance. The ideal candidate will have 2+ years of experience in ML infrastructure, MLOps, or ML systems engineering. Strong written communication skills and the ability to explain complex technical decisions clearly are required.

Key Highlights
Guide research and engineering teams
Improve AI model performance
Design challenging tasks and write accurate solutions
Key Responsibilities
Guide research and engineering teams
Design challenging tasks and write accurate solutions
Evaluate MLOps tasks and solutions
Technical Skills Required
JAX PyTorch GPU kernels Pallas Triton
Benefits & Perks
$90-$140/hour
Remote work
40 hours/week

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: MLOps Engineer Expert

Type: Contract

Compensation: $90–$140/hour

Location: Remote

Commitment: 40 hours/week

Role Responsibilities

  • Guide research and engineering teams to close knowledge gaps and improve AI model performance in MLOps, training infrastructure, and ML framework-level topics.
  • Design challenging, domain-relevant tasks, and write accurate and well-structured solutions to MLOps and ML systems problems.
  • Evaluate MLOps tasks and solutions and provide clear, written technical feedback.
  • Develop guidelines and detailed rubrics/evaluation frameworks to assess training pipeline design, distributed systems reasoning, and kernel-level optimization across tasks.
  • Collaborate with other subject matter experts to ensure consistency and accuracy in training data.

Qualifications

Must-Have

  • 2+ years of dedicated professional experience in ML infrastructure, MLOps, or ML systems engineering at a recognized, top-tier organization.
  • Hands-on production experience with JAX and/or PyTorch at scale.
  • Experience writing or optimizing custom GPU kernels using Pallas (JAX) or Triton.
  • Demonstrable career progression.
  • Ability to engage reliably for at least 40 hours/week during weekdays.
  • Strong written communication skills and the ability to explain complex technical decisions clearly.

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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