MLOps Engineer - AI Specialist

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, 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.