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

About the job Work Snapshot Type: W2 Location: Remote Commitment: 40 hours per week Commission: $35-$45 per hour What You Ll Be Doing Design and evaluate complex MLOps and ML systems tasks across training infrastructure and distributed systems Develop structured solutions, evaluation rubrics, and optimization frameworks for training pipelines and kernel-level workloads Provide detailed written feedback on ML systems and infrastructure-related tasks Collaborate with engineering teams and subject matter experts to improve training data quality and consistency Support performance improvements across model training infrastructure and framework-level systems What We Re Looking For Strong experience in ML infrastructure, MLOps, or ML systems engineering Strong experience in JAX and/or PyTorch within production-scale environments Strong experience in custom GPU kernel optimization using Pallas or Triton Strong written communication skills with the ability to explain complex technical decisions clearly Ability to contribute consistently during weekday working hours How To Apply Upload resume Interview Submit form Desired Skills and Experience Writing, pytorch, ML infrastructure, MLOps, ML systems engineering, JAX, optimizing custom GPU kernels