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

Role Overview

MLOps Engineer (Remote, US) working on large-scale ML infrastructure to support next-generation AI/GenAI initiatives. You’ll improve model performance and contribute to highly scalable training environments through MLOps, distributed training, and framework-level engineering.

Responsibilities

• Support AI research and engineering teams in improving ML infrastructure and training systems
• 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 engineering career progression in ML/AI infrastructure roles
• Ability to work a full-time 40 hours/week weekday schedule (no conflicting full-time engagements)
• Strong written communication and technical documentation skills

Nice-to-Haves

• None explicitly stated

Engagement & Logistics

• W2, full-time contingent role; remote within the United States
• Application includes resume submission, a ~15-minute AI interview, and follow-up onboarding steps