ML Systems Engineer - Fully Remote | Upto $110/hr

mercor; United States; Remote; USD 96,000 - 152,000; Part time

Job summary

Mercor, headquartered in San Francisco, seeks an MLOps Engineer for a remote contract role. You will guide research and engineering teams on ML infrastructure, training pipelines, and framework-level optimization to push model performance.

The candidate should have 2+ years in ML infrastructure or MLOps at top-tier organizations, hands-on experience with JAX and/or PyTorch at scale, and kernel experience with Pallas (JAX) or Triton.

Qualifications

• 2+ years of dedicated professional experience in ML infrastructure, MLOps, or ML systems engineering.
• 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.

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.

Skills

MLOps

JAX

PyTorch

Kernel optimization

Strong communication

Tools

Pallas

Triton

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: $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 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.