MLOps Engineer (JAX, PyTorch, Pallas/Triton) [$35-$45/hr] [W2, Contingent Role]
Talented MLOps Engineers with deep, hands-on expertise in modern ML frameworks specifically JAX, PyTorch, and kernel-level programming (Pallas/Triton)
This is a W-2 employment position requiring a commitment of 40 hours per week (during weekdays)
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Role Responsibilities
- Guide research and engineering teams to close knowledge gaps and improve AI model performance in MLOps, training infrastructure, and ML framework-level topics
- Design challenging, domain-relevant tasks, and write accurate and well-structured solutions to MLOps and ML systems problems
- Evaluate MLOps tasks and solutions and provide clear, written technical feedback
- Develop guidelines and detailed rubrics/evaluation frameworks to assess training pipeline design, distributed systems reasoning, and kernel-level optimization across tasks
- Collaborate with other subject matter experts to ensure consistency and accuracy in training data
Good Candidature
- 2+ years of dedicated professional experience in ML infrastructure, MLOps, or ML systems engineering at a recognized, top-tier organization
- Hands-on production experience with JAX and/or PyTorch at scale
- Experience writing or optimizing custom GPU kernels using Pallas (JAX) or Triton
- Demonstrable career progression
- Ability to engage reliably for at least 30 hours/week during weekdays
- Strong written communication skills and the ability to explain complex technical decisions clearly
