Sr. Manager , Annapurna Labs - Cloud Scale Machine Learning Acceleration Team

Amazon Amazon · Big Tech · Tempe, AZ · Software Development

This role is for a Sr. Manager to lead a team of SOC integration engineers responsible for critical deliverables in ML accelerator chips. The focus is on designing and optimizing hardware for AWS Machine Learning servers, specifically mentioning AWS Inferentia for inference. The role involves driving technical decisions, ensuring on-time delivery, and establishing best practices for top-level integration. While the role is in AI hardware acceleration, it's not directly building ML models but rather the infrastructure that runs them.

What you'd actually do

  1. Lead and grow a team of SOC integration engineers responsible for critical deliverables in our ML accelerator chips
  2. Drive technical decisions across multiple disciplines (RTL, timing, DFT, physical design)
  3. Ensure on-time delivery of complex SOC integration milestones
  4. Establish and maintain best practices for top-level integration, including clock/reset architecture, CDC methodology, and quality metrics
  5. Interface with various stakeholders including architecture, verification, and physical design teams

Skills

Required

  • 7+ years of engineering team management experience
  • Knowledge of SoC architecture
  • 15+ years writing functional or performance models for SoCs, CPUs, GPUs, or ASICs
  • Strong C++ and/or SystemC skills in large-scale OOP codebases

Nice to have

  • Master's degree in electrical engineering, computer engineering, or equivalent
  • Experience with ML accelerator or high-performance compute SOC development
  • Track record of implementing and scaling SOC integration methodologies
  • Strong background in power/performance optimization and physical design considerations
  • Experience with modern SOC development tools and flows

What the JD emphasized

  • ML accelerator chips
  • successful tape-outs
  • ML accelerator or high-performance compute SOC development

Other signals

  • custom chips, accelerators, and software stacks
  • ML accelerator chips
  • AWS Inferentia, our custom designed machine learning inference datacenter server
  • hardware in our data centers
  • SOC integration engineers
  • ML accelerator or high-performance compute SOC development