Design and build distributed evaluation platforms for large-scale ML evaluation workloads.
Profile evaluation platforms to identify bottlenecks and optimize inference speed and resource use.
Collaborate with ML engineers to understand evaluation needs and improve DevX of evaluation
Improve runtime goodput of ML inference workloads and efficiency of metric computations.
Implement and maintain ML infra tools (ML Pathways, JAX, Flume, TensorFlow).

🎯 Requirements

B.S. in Computer Science, Math, or 3+ years of experience.
Proficient in distributed systems design with ML efficiency focus.
Experience with ML frameworks (TensorFlow, JAX, XLA).
Strong Python and C++ programming skills.
Practical familiarity with profiling tools to find performance bottlenecks.

🎁 Benefits

Participation in discretionary annual bonus program and equity incentives.
Generous company benefits program subject to eligibility.

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