Senior ML Hardware-Software Co-Design Engineer

Google; Sunnyvale (CA); On-site; USD 192,000 - 278,000; Full time

Job summary

Google in Sunnyvale, CA, is seeking an experienced HPC/ML hardware architect to shape the future of AI/ML hardware acceleration, focusing on TPU architecture integration into AI/ML systems.

You will collaborate across AI research, hardware design, and software teams to drive performance modeling, verification, and scalable accelerator development for large ML models. The role offers high-impact work in a fast-growing field with cutting-edge silicon design.

Qualifications

• Bachelor's degree required in EE/CE/CS or related field.
• 10 years of experience in computer architecture, chip architecture, or hardware-software co-design.
• Experience developing systems for performance modeling, simulation, or system analysis.

Responsibilities

• Drive the definition and optimization of the hardware/software stack for training and serving large ML models.
• Collaborate with research and modeling teams to innovate on model architectures and their impact on hardware performance.
• Lead development of configurable architectural simulators and cycle-accurate performance models.
• Conduct system-level performance analysis across highly distributed ML systems and balance compute, memory bandwidth, and inter-chip networks.
• Engage with hardware design, compiler development, and ML research to translate innovations from concept to production.

Skills

ML hardware design

Performance modeling

System integration

Cross-functional collaboration

Education

Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or related field

Master's degree or PhD in Electrical Engineering, Computer Engineering or Computer Science with emphasis on computer architecture

Tools

TensorFlow

PyTorch

Job description

Google in Sunnyvale, CA, is seeking an experienced HPC/ML hardware architect to shape the future of AI/ML hardware acceleration, focusing on TPU architecture integration into AI/ML systems.

You will collaborate across AI research, hardware design, and software teams to drive performance modeling, verification, and scalable accelerator development for large ML models. The role offers high-impact work in a fast-growing field with cutting-edge silicon design.