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

Role Overview

MLOps Engineer supporting next-generation AI systems through large-scale ML infrastructure, training optimization, and framework-level engineering. You’ll work with AI research and engineering teams on GenAI initiatives, improving model performance and building highly scalable training environments.

Responsibilities

• Support AI research/engineering teams to improve ML infrastructure and training systems
• Design advanced MLOps and ML systems with structured technical solutions
• Evaluate ML system outputs and provide detailed technical feedback
• Build 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 or optimizing GPU kernels using Pallas or Triton
• Strong understanding of ML training systems and distributed infrastructure
• Proven engineering/AI infrastructure career progression
• Ability to work a full-time 40 hours/week weekday schedule with no conflicting full-time commitments
• Strong written communication and technical documentation skills

Nice to Have

• Not explicitly stated.

Engagement & Location

• W2, full-time contingent engagement (40 hours/week)
• Remote within the United States