Silicon Engineer

Anthropic Anthropic · AI Frontier · San Francisco, CA · AI Research & Engineering

Anthropic is building a custom silicon team to design and ship silicon for their large-scale AI training and inference workloads. This role involves end-to-end activities from strategy and specification to execution and technical bar setting, with a focus on hardware-software co-design and partner collaboration.

What you'd actually do

  1. Take part in end to end activities for the program: strategy, specification, execution and the technical bar.
  2. Write the specifications and interface definitions that others design against and keep them coherent as the architecture converges
  3. Make and own directional calls: technology and IP selection, where we build versus buy versus license, and where we take design authority versus rely on partners
  4. Build and share AI-assisted approaches to the code-like parts of your domain, and help the team learn what Claude can genuinely accelerate
  5. Partner with Anthropic's inference, performance, kernels, and infrastructure teams on hardware-software co-design, and with our hardware systems team on bring-up and integration

Skills

Required

  • Deep, hands-on expertise in at least one silicon domain: front-end design, pre-silicon verification, physical design, design for test, analog and mixed-signal, technology and foundry, design infrastructure, or packaging and signal/power integrity
  • Working fluency in the domains adjacent to your own, sufficient to reason about chip-level tradeoffs outside your specialty
  • Experience working with external partners — ASIC houses, IP vendors, foundries, or test partners — including reviewing their work and holding a technical bar
  • Practical experience using AI coding tools in your own work, and clear ideas about where they help and where they do not
  • Clear written and verbal communication, and experience driving alignment across teams and organizations
  • Comfort operating with high autonomy and little scaffolding on a highly dynamic program

Nice to have

  • Experience on machine learning accelerators, high-performance compute, or other large, high-bandwidth designs
  • Experience on a founding or early-stage silicon team, including standing up flows, methodology, or tooling from nothing
  • Experience with both partner-executed and fully in-house programs, and a view on the tradeoffs between them
  • Familiarity with the chip-package-system interface and the tradeoffs that cross it
  • Experience with hardware-software co-design and working directly with compiler, kernel, or runtime teams
  • Experience building or extending AI-assisted design, verification, or physical design flows
  • Depth in memory subsystems, on-die interconnect, numerics, or low-power design

What the JD emphasized

  • shipped silicon
  • realistic relationship with schedules
  • comfortable making consequential calls without a large organization behind them
  • Direct personal contribution to silicon that taped out and shipped, with ownership you can speak to in detail
  • Track record of owning directional technical decisions and their consequences, not only making recommendations