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

This role focuses on advancing AI systems through large-scale ML infrastructure and training optimization. The MLOps Engineer will support GenAI initiatives, design solutions, and contribute to scalable training environments.

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

• 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