Remote ML Systems Engineer — PyTorch & AI Trainer

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

Job summary

Mercor is seeking a PyTorch Expert for a remote contract role. You will work with research and engineering teams to advance AI model performance across MLOps and training infrastructure. This position requires hands-on PyTorch experience at scale, kernel-level optimization, and strong written communication skills.

The role includes a 40-hour workweek and compensation in the USD hourly range. You will collaborate with subject matter experts to ensure high-quality training data and robust ML

Qualifications

• 2+ years of dedicated professional experience in ML infrastructure, MLOps, or ML systems engineering.
• Hands-on production experience with PyTorch at scale.
• Experience writing or optimizing custom GPU kernels using Triton or Pallas.
• 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.

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

PyTorch at scale

ML infrastructure

MLOps

ML systems engineering

Strong written communication

40 hours/week availability

GPU kernel optimization

Tools

Triton

Pallas

Job description

Mercor is seeking a PyTorch Expert for a remote contract role. You will work with research and engineering teams to advance AI model performance across MLOps and training infrastructure. This position requires hands-on PyTorch experience at scale, kernel-level optimization, and strong written communication skills.

The role includes a 40-hour workweek and compensation in the USD hourly range. You will collaborate with subject matter experts to ensure high-quality training data and robust ML