MLOps Engineer

We're seeking talented MLOps Engineers with deep, hands-on expertise in modern ML frameworks — specifically JAX, PyTorch, and kernel-level programming (Pallas/Triton). This role involves AI model training and evaluation work, including writing and assessing MLOps tasks and solutions to generate high-quality training data for frontier AI systems.

This is a 40-hour full-time engagement, with no conflicts/no other engagements.

Key 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.

Core Qualifications

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.