MLOps Engineer (JAX, PyTorch, Pallas/Triton) | Remote

Work Snapshot
Type: W2
Location: United States
Commitment: ~30+ hours/week
What You Ll Be Doing
Guide engineering and research teams on MLOps, ML infrastructure, and training system optimization
Design challenging tasks and develop structured solutions for ML systems and infrastructure workflows
Evaluate MLOps tasks and provide detailed technical feedback
Develop evaluation frameworks for training pipelines, distributed systems, and kernel-level optimization
Work on large-scale AI model infrastructure using modern ML frameworks
Collaborate with subject matter experts to ensure accuracy and consistency in training data
What We Re Looking For
Strong experience in ML infrastructure, MLOps, or ML systems engineering
Strong experience with JAX and/or PyTorch in production environments
Strong experience in writing or optimizing GPU kernels using Pallas or Triton
Strong understanding of distributed systems and training pipeline design
Strong analytical and problem-solving skills in ML systems optimization
Ability to communicate complex technical decisions clearly in written form
Ability to work consistently during weekdays in a remote environment
How To Apply
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Work arrangement
Yes