MLOps Engineer - JAX/PyTorch Expert

Job Description 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 (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.

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