Senior Silicon System and Software Integration Engineer, Google Cloud

Google Google · Big Tech · Sunnyvale, CA +1

This role focuses on the hardware-software integration and validation of AI/ML hardware accelerators (TPUs) for Google Cloud. The engineer will work on ASIC development, validation, software, tools, and methodologies to ensure the functionality and performance of these custom silicon solutions that power Google's AI/ML applications.

What you'd actually do

  1. Review chip specifications and designs, developing integration plans with software and system partners while coordinating hardware/software delivery.
  2. Lead the bringup of ML compute features, integrating and validating complex hardware/software designs, including third-party IPs. Develop validation firmware to verify hardware functionality.
  3. Execute hardware-software co-simulation methodologies leveraging RTL, emulation, and field-programmable gate array (FPGA) environments. Utilize architectural simulators and performance models to correlate results.
  4. Design validation tests and microbenchmarks to verify IP functionality and performance. Author comprehensive test plans in coordination with cross-functional teams including Design, Design Verification (DV), Firmware, and Architecture.
  5. Own debug discussions with Design/DV/Software/Architecture teams and help root cause functional failures and performance issues throughout the product development cycle. Improve validation coverage and sign-off processes for high-quality tapeout and production deployment.

Skills

Required

  • Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field, or equivalent practical experience.
  • 5 years of experience in at least two of the following: computer architecture, embedded firmware, ASIC design or verification, or the integration and enablement of first/third party IPs.
  • Experience in hardware/software integration and validation.
  • Experience with register-transfer level (RTL) development, design verification, and evaluation.

Nice to have

  • Master's degree or PhD in Electrical Engineering, Computer Engineering or Computer Science, with an emphasis on computer architecture.
  • 4 years of experience with C++/Python software design principles.
  • Experience integrating complex hardware/software systems in accelerators.
  • Experience developing firmware for embedded systems or accelerators.
  • Experience in debugging firmware using simulation tools.
  • Knowledge of real-time operating system (RTOS) internals.

What the JD emphasized

  • AI/ML hardware acceleration
  • TPU technology
  • custom silicon solutions
  • hardware-software integration
  • ML compute IP
  • ASIC development
  • validation
  • software
  • tools
  • methodologies
  • chip development
  • hardware-software integration and validation
  • end-to-end hardware-software integration and validation
  • hardware, software, and system functionality and performance
  • chip team
  • silicon development criteria
  • chip and system schedules
  • production
  • silicon and system validation environments
  • specification, design, and verification teams
  • compiler and performance teams
  • ML compute IP
  • functional and performant hardware and software systems
  • coordination, debugging, and enablement of the platform
  • AI and Infrastructure team
  • AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity
  • Google's groundbreaking innovations
  • cutting-edge AI models
  • computing power
  • essential platforms
  • hyperscale computing
  • TPUs
  • Vertex AI for Google Cloud
  • Google Global Networking
  • Data Center operations
  • systems research
  • chip specifications and designs
  • integration plans
  • software and system partners
  • hardware/software delivery
  • ML compute features
  • complex hardware/software designs
  • third-party IPs
  • validation firmware
  • hardware functionality
  • hardware-software co-simulation methodologies
  • RTL, emulation, and field-programmable gate array (FPGA) environments
  • architectural simulators and performance models
  • validation tests and microbenchmarks
  • IP functionality and performance
  • test plans
  • Design, Design Verification (DV), Firmware, and Architecture
  • debug discussions
  • Design/DV/Software/Architecture teams
  • root cause functional failures and performance issues
  • product development cycle
  • validation coverage and sign-off processes
  • high-quality tapeout and production deployment
  • Electrical Engineering, Computer Engineering, Computer Science
  • computer architecture, embedded firmware, ASIC design or verification, or the integration and enablement of first/third party IPs
  • hardware/software integration and validation
  • register-transfer level (RTL) development, design verification, and evaluation
  • computer architecture
  • C++/Python software design principles
  • complex hardware/software systems in accelerators
  • firmware for embedded systems or accelerators
  • debugging firmware using simulation tools
  • real-time operating system (RTOS) internals

Other signals

  • AI/ML hardware acceleration
  • TPU technology
  • custom silicon solutions
  • hardware-software integration
  • ML compute IP