Hardware/Software Co-Design Engineer, Inference

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

In most instances, this position requires in-person interviews as part of the hiring process.

Minimum qualifications

• Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field, or equivalent practical experience.
• 10 years of experience in computer architecture, chip architecture, or hardware-software co-design.
• Experience developing systems for performance modeling, simulation, or system analysis.

Preferred qualifications

• Master's degree or PhD in Electrical Engineering, Computer Engineering or Computer Science, with an emphasis on computer architecture.
• Experience architecting hardware solutions or performance optimizations for ML training and inference.
• Experience with deep learning frameworks such as TensorFlow or PyTorch.
• Deep understanding of ML trends, business drivers, and the software ecosystem.
• Ability to engage and collaborate with hardware designers, software architects, and ML researchers.

About The Job

In this role, you’ll work to shape the future of AI/ML hardware acceleration. You will have an opportunity to drive cutting‑edge TPU (Tensor Processing Unit) technology that powers Google’s most demanding AI/ML applications. You’ll be part of a team that pushes boundaries, developing custom silicon solutions that power the future of Google’s TPU. You'll contribute to the innovation behind products loved by millions worldwide, and leverage your design and verification expertise to verify complex digital designs, with a specific focus on TPU architecture and its integration within AI/ML‑driven systems.

In this role, you will act as a key technical anchor bridging the gap between model architecture innovation and next‑generation hardware design. Operating cross‑functionally across AI research and engineering, you will help shape the architectural roadmap for our future machine learning serving and training capabilities. You will drive the integration of Machine Learning (ML) research such as the training and serving of massive foundation models with advanced silicon architectures to deliver industry‑leading, high‑performance, and power‑efficient accelerators.

The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.

We’re the driving force behind Google’s groundbreaking innovations, empowering the development of our cutting‑edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world‑leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.

Individual pay is determined by factors including job‑related skills, experience, and relevant education or training.

US: $192000 - $278000 (USD) + 20% bonus target + equity + benefits

Responsibilities

Learn more about benefits at Google .

• Drive the definition and optimization of the hardware/software stack to enable performant training and serving of large ML models.
• Collaborate with research and modeling teams to innovate on model architectures, focusing on scaling, quality, and their direct impact on hardware performance.
• Lead the development of configurable architectural simulators and cycle‑accurate performance models to quantify microarchitectural optimizations and evaluate architectural decisions.
• Conduct system‑level performance analysis across highly distributed ML systems, innovating new methodologies to balance compute, memory bandwidth, and inter‑chip network requirements.
• Engage with partners across hardware design, compiler development, and ML research to transition architectural innovations from concept to production.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form .