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 Robust 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

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📌 MLOps Engineer (JAX, PyTorch, Pallas/Triton) | Remote (India)
🏢 Crossing Hurdles
📍 India