MLOps Engineer - AI Trainer

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: JAX Expert
Type: Contract
Compensation: $70–$110/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, 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 at scale.

- Experience writing or optimizing custom GPU kernels using Pallas 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:

- For any help or support, reach out to:

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.

#hiring mercor
Originally posted on Himalayas