Head of Inference Performance Visibility

Highlights

• Define how performance is understood across next-gen AI accelerator systems.
• Build cluster-scale analysis for distributed inference across data center networks.
• Shape telemetry and counter models that link silicon signals to workload behavior.

What they offer

• Medical, dental, and vision packages with generous premium coverage
• Housing subsidy of $2.5k per month for those living within walking distance of the office
• Relocation support for those moving to San Jose
• Various wellness benefits covering fitness, mental health, and more
• Daily lunch and dinner in the office
• Unlimited compute budget subject to ROI justification

Ideal candidate

Systems-minded builder who has owned profiling or observability systems end-to-end and loves connecting low-level hardware behavior to large-scale distributed ML performance. You thrive at the hardware-software boundary leading foundational architecture.

Requirements

• Deep experience building complex systems at the intersection of hardware and software
• Personally envisioned and built significant portions of profiling, tracing, or observability systems
• Ability to translate raw hardware signals into production-grade telemetry and analysis infrastructure
• Experience correlating time-series events across distributed systems
• Deep systems programming expertise in C++ or Rust shipping low-level infrastructure
• Experience designing distributed correlation, timestamp-alignment, or performance modeling frameworks
• Experience designing distributed tracing or observability platforms at scale
• Experience with high-performance computing systems and large AI clusters
• Experience with hardware counter design and instrumentation strategy
• Experience with performance modeling for large-scale ML workloads
• Experience leading cross-functional architectural initiatives spanning hardware and software