MLOps Engineer | Remote | $90 –$140/hr

Role Overview

MLOps Engineer to advance next-generation AI systems by building and optimizing large-scale ML infrastructure and training pipelines. You’ll support GenAI initiatives, improve model performance, and help engineer highly scalable AI training environments.

Responsibilities

• Support AI research and engineering teams with ML infrastructure and training system improvements
• Design advanced MLOps/ML systems with accurate, structured technical solutions
• Evaluate ML system outputs and provide detailed technical feedback
• Develop evaluation rubrics/frameworks for distributed systems, training pipelines, and kernel-level optimization
• Collaborate with domain experts to maintain consistency and quality across AI training workflows
• Improve large-scale model training performance and infrastructure reliability

Requirements

• 2+ years of 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 GPU kernels using Pallas or Triton
• Strong understanding of ML training systems and distributed infrastructure
• Demonstrated career progression in engineering or AI infrastructure roles
• Ability to commit to a full-time 40-hour/week weekday schedule
• Strong written communication and technical documentation skills

Nice-to-Haves

• None explicitly stated

Engagement Details

• W2, full-time contingent role
• Remote (United States)
• 40 hours/week, no conflicting full-time engagements permitted