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Head of Inference Performance Visibility

Etched· Architecture
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San Jose$200k - $400kFull-timePosted 3mo ago

About the role

Head of Performance Visibility to define how performance is understood across next-generation AI accelerator systems, spanning hardware, software, runtimes, and distributed inference environments. Establishes metrics, abstractions, and tooling to surface performance intelligence for large-scale AI systems and multi-device deployments.

Responsibilities

  • Define the architectural approach for collecting and structuring telemetry across CPUs, drivers, interconnects, and multiple accelerators
  • Design scalable models for correlating performance events across device and host boundaries
  • Develop mechanisms to align hardware counters, runtime activity, communication phases, and workload semantics across model-layer execution into coherent, actionable insight
  • Implement time synchronization and trace-alignment strategies across multi-device systems
  • Define structured counter taxonomies separating base signals from derived metrics
  • Design derived performance models bridging low-level hardware signals and workload-level behavior
  • Influence instrumentation strategy for future hardware generations
  • Build tools that identify bottlenecks among multi-accelerator workloads across chips within hosts
  • Build cluster-scale performance analysis for distributed inference across data center networks
  • Contribute to analysis engines and developer-facing tooling that transform raw telemetry into intuitive insight
  • Shape how performance intelligence is surfaced to engineers debugging large-scale AI systems

Qualifications

  • 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 scalable telemetry and analysis infrastructure
  • Experience correlating time-series events across distributed systems
  • Deep systems programming expertise (C++ or Rust) with a track record of shipping low-level infrastructure
  • Experience designing distributed correlation mechanisms, timestamp-alignment strategies, or performance modeling frameworks across multiple devices or hosts
  • Experience designing distributed tracing or observability platforms at scale
  • Experience with high-performance computing systems and large AI training clusters
  • Experience with timestamp synchronization strategies and event alignment in distributed environments
  • 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 teams

Skills

Required:Telemetry and observability designDistributed systems performance analysisTime-series data correlationC++ or Rust

Benefits

  • Medical, dental, and vision packages with generous premium coverage
  • $500 per month credit for waiving medical benefits
  • Housing subsidy of $2.5k per month for those living within walking distance of the office
  • Relocation support for those moving to San Jose (Santana Row)
  • Various wellness benefits covering fitness, mental health, and more
  • Daily lunch and dinner in our office
  • Unlimited compute budget subject to ROI justification
Last updated Oct 15, 2026. Interested? Apply on the company site.
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About Etched

Etched is building frontier inference clusters: co-designs chips, racks, software and manufacturing to push the pareto frontier for AI hardware.

frontier inference clustersAI hardwarechipsrackssoftwaremanufacturingparto frontier
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