Head of Inference Performance Visibility
Etched · San Jose
About this role
## About Etched Etched is building hardware for frontier intelligence. We co-design chips, racks, software, and manufacturing to deliver best-in-class throughput and latency across both prefill and decode workloads. Our first products are heavily focused on inference, backed by hundreds of millions from top-tier investors and staffed by leading engineers. ## Role: Head of Inference Performance Visibility We’re hiring a **Head of Performance Visibility** to define how performance is understood across next-generation AI accelerator systems. At Etched, performance at this scale is not just a device-level question—it’s a **high-performance distributed systems problem**. You’ll define performance metrics that connect raw hardware signals to distributed workload context, ML cluster dynamics, pod communication patterns, and emergent bottlenecks. This role goes beyond telemetry: you’ll establish new abstractions, structured counter ontologies, cross-layer event correlation frameworks, distributed time-alignment strategies, and scalable reasoning systems operating across nodes, racks, and clusters. ## Key Responsibilities ### System-Level Performance Design - 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** ### Cross-Layer Event Correlation - Align hardware counters, runtime activity, communication phases, and workload semantics into coherent, actionable insight - Implement time synchronization and trace-alignment strategies across **multi-device systems** ### Telemetry & Counter Modeling - 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 ### Distributed Performance Reasoning - Build tools to identify bottlenecks among multi-accelerator workloads across chips within hosts - Build cluster-scale performance analysis for distributed inference across data center networks ### Tooling & Insight Delivery - 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 ## You Might Be a Good Fit If You Have - 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**) with a track record of shipping low-level infrastructure close to hardware/runtime systems - Experience designing distributed correlation mechanisms, timestamp-alignment strategies, or performance modeling frameworks across multiple devices/hosts - Experience designing distributed tracing/observability platforms at scale - Experience with high-performance computing systems and large AI training clusters - Experience with timestamp synchronization and event alignment in distributed environments - Experience with hardware counter design and instrumentation strat
Listing freshness
CronJobs last confirmed this listing 2h ago. If its source stops confirming the opening for seven days, this page is removed from active inventory.