Performance Architect, AI Hw

Tenstorrent · Semiconductors · Toronto, ON · Tensix

Role focuses on analyzing and optimizing AI workloads on hardware architecture (Tensix) to improve performance, power, and area. Involves developing performance models, simulators, and collaborating with RTL, Compiler, and Runtime teams. Connects architecture, software, and RTL for next-gen AI systems.

What you'd actually do

  1. Benchmark and analyze complex AI workloads across single and multi-node hardware configurations to guide next-gen architecture.
  2. Develop and maintain performance models, simulators, and micro-benchmark suites to drive feature evaluation and design optimization.
  3. Conduct detailed PPA (Performance, Power, Area) studies to assess design tradeoffs and inform hardware-software co-design decisions.
  4. Collaborate closely with RTL, Compiler, and Runtime teams to instrument and correlate performance models with silicon results.

Skills

Required

  • C++
  • Python
  • simulation
  • modeling
  • performance analysis
  • heterogeneous compute systems
  • deep learning workloads
  • architectural insight
  • design tradeoffs

Nice to have

  • RISC-V CPU
  • RTL
  • Compiler
  • Runtime
  • PPA (Performance, Power, Area) studies

What the JD emphasized

  • AI workloads
  • performance models
  • hardware features
  • AI systems
  • performance gains
  • AI and ML workloads
  • AI accelerators
  • compute architecture design
  • performance tuning
  • performance features
  • performance analysis

Other signals

  • AI workload behavior
  • performance models
  • hardware features
  • AI systems