MLOps Engineer | Remote | $70 –$110/hr

Role overview

MLOps Engineer (Remote, US) supporting next-generation GenAI via large-scale ML infrastructure, training optimization, and framework-level engineering. You’ll help improve model performance and build/reliably operate highly scalable AI training environments.

Responsibilities

• Support AI research and engineering teams with ML infrastructure and training system improvements
• Design advanced MLOps and ML systems with accurate, structured technical solutions
• Evaluate ML system outputs and provide detailed technical feedback
• Create evaluation rubrics/frameworks for distributed systems, training pipelines, and kernel-level optimization
• Collaborate with domain experts to ensure 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/optimizing GPU kernels using Pallas or Triton
• Strong understanding of ML training systems and distributed infrastructure
• Demonstrated progression in engineering/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

• (Not explicitly stated beyond the above)

Engagement details

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