Head of Inference Performance Visibility

The role

You will define how performance is understood across next-generation AI accelerator systems. This involves defining performance metrics that connect hardware signals to distributed workload context and building tools to identify bottlenecks across multi-accelerator workloads.

What you will do

• 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
• 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

Required 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
• Demonstrated ability to translate raw hardware signals into scalable, production-grade telemetry and analysis infrastructure
• Experience correlating time-series events across distributed systems
• Deep systems programming expertise (C++ or Rust)
• Track record of shipping low-level infrastructure operating close to hardware or runtime systems
• 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

Nice to have

• Experience leading cross-functional architectural initiatives spanning hardware and software teams

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

About the company

Etched is building hardware for frontier intelligence by co-designing chips, racks, software, and manufacturing. They are a fully in-person team in San Jose (Santana Row).