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

Role Overview

MLOps Engineer (Remote, United States) focused on advancing next-generation AI systems through large-scale ML infrastructure, training optimization, and framework-level engineering. You’ll support GenAI initiatives by improving model performance and building/maintaining highly scalable AI training environments.

Responsibilities

• Support AI research and engineering teams to improve ML infrastructure and training systems
• Design MLOps and ML systems components 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 and/or Triton
• Strong understanding of ML training systems and distributed infrastructure
• Demonstrated engineering/AI infrastructure career progression
• Ability to commit to full-time 40 hours/week on weekdays with no conflicting full-time work
• Strong written communication and technical documentation skills

Nice-to-Haves

• Experience across evaluation frameworks and distributed training pipeline benchmarking

Engagement Details

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

Hiring Process

• Upload resume
• 15-minute AI interview (conversation to assess background/technical expertise)
• Follow-up communication with next steps and onboarding