[Hiring] MLOps Engineer - JAX/PyTorch Expert @Mercor

Role Description

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

• 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.

Requirements

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

Application Process

• Upload resume
• AI interview based on your resume
• Submit form

Resources & Support

• For details about the interview process and platform information, please check: Interview Process
• For any help or support, reach out to: [email protected]
• Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.