MLOps Engineer - JAX/PyTorch Expert

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 (JAX, PyTorch, Pallas/Triton)

• Type: Contract
• Compensation: $90--$130/hour
• Location: Remote

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 across multiple specializations. Write accurate and well-structured solutions to MLOps and ML systems problems.
• Evaluate MLOps tasks and solutions. 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

• 5 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, including distributed training strategies (FSDP, tensor parallelism, pipeline parallelism), memory optimization, and framework-level debugging.
• Experience writing or optimizing custom GPU kernels using Pallas (JAX) or Triton, including tiling strategies, memory layout design, and kernel fusion.
• Demonstrable career progression.
• Ability to engage reliably for at least 30 hours/week during weekdays.
• Strong written communication skills and the ability to explain complex technical decisions clearly.

Compensation & Legal

• W-2 employment with Cincinnatus LLC.
• Equal Employment Opportunity employer.

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: [email protected]

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