Senior Staff Software Engineer, AI/ML Diagnostic Systems and Hardware Coverage

Responsibilities

The role involves architecting generative AI tools and agentic workflows to optimize hardware diagnostic software across Google's compute and storage infrastructure. You will serve as a technical authority, driving the convergence of AI, silicon design analysis, and systems engineering to ensure hardware reliability.

Requirements

Candidates must have at least 8 years of software development experience, including 7 years in technical project strategy and machine learning design. A bachelor's degree is required, with a preference for a master's degree in Computer Science, Electrical Engineering, or Artificial Intelligence.

Skills

• Software development
• Machine learning
• Technical project strategy
• Model deployment
• Data processing
• Hardware diagnostics
• C++
• Rust
• Computer architecture
• ASIC
• SoC
• Generative AI
• System telemetry
• Infrastructure systems
• Deep learning
• Distributed computing

Benefits

• Bonus
• Equity
• Health Insurance

About this role

MINIMUM QUALIFICATIONS:

* Bachelor’s degree or equivalent practical experience.
* 8 years of experience in software development.
* 7 years of experience leading technical project strategy, ML design, and
end-to-end Machine Learning (e.g., model deployment, model evaluation, data
processing, debugging).
* 5 years of experience with design and architecture; and testing/launching
software products.
* 5 years of experience with one or more of the following: Speech/audio (e.g.,
technology duplicating and responding to the human voice), reinforcement
learning (e.g., sequential decision making), ML infrastructure, or
specialization in another ML field.
* Experience in designing, implementing and troubleshooting hardware
diagnostics.

PREFERRED QUALIFICATIONS:

* Master’s degree in Computer Science, Electrical/Computer Engineering,
Artificial Intelligence, or equivalent practical experience.
* 10 years of professional software engineering and machine learning
experience, including technical leadership on infrastructure systems.
* 8 years of experience with data structures/algorithms.
* Experience building production machine learning systems, agentic
architectures, LLM pipelines, or deep learning models applied to system
telemetry.
* Advanced experience in C++ or Rust, along with experience using machine
learning frameworks and data processing tools.
* Knowledge of computer architecture, modern ASIC/SoC functional blocks,
high-speed interfaces, and hardware failure mechanisms.

ABOUT THE JOB:

Google's software engineers develop the next-generation technologies that change
how billions of users connect, explore, and interact with information and one
another. Our products need to handle information at massive scale, and extend
well beyond web search. We're looking for engineers who bring fresh ideas from
all areas, including information retrieval, distributed computing, large-scale
system design, networking and data storage, security, artificial intelligence,
natural language processing, UI design and mobile; the list goes on and is
growing every day. As a software engineer, you will work on a specific project
critical to Google’s needs with opportunities to switch teams and projects as
you and our fast-paced business grow and evolve. We need our engineers to be
versatile, display leadership qualities and be enthusiastic to take on new
problems across the full-stack as we continue to push technology forward.

The Platforms Infrastructure Engineering Core Systems and Capacity Assurance
team is responsible for delivering the tools and systems that manage the state
of a machine throughout it's service lifetime while part of the Google Fleet. We
are also responsible for the diagnostic tests, and repair strategies to ensure
that a machine is healthy and ready to serve. This includes software
installation, hardware health testing, and machine management. We are
responsible for the validation of machine health at the time of manufacture and
also when it is deployed in the data center.

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: $262000 - $364000 (USD) + 25% bonus target + equity + benefits

Learn more about benefits at Google
[https://www.google.com/about/careers/applications/benefits/].

RESPONSIBILITIES:

* Serve as the technical authority driving the convergence of Artificial
Intelligence, silicon/hardware design analysis, and systems engineering.
* Architect and build generative AI tools, foundation model skills, and agentic
workflows by leveraging complex ASIC architectural specifications, system
schematics, software contracts, and historical test execution telemetry.
* Transform how hardware diagnostic software is created, optimized, and
deployed across Google’s next-generation compute, accelerator (TPU/GPU),
network, and storage infrastructure.
* Empower Diagnostic Software Engineers to achieve comprehensive test coverage
across all hardware components, interfaces, and functional blocks.
* Optimize test execution time and pinpoint optimal repair actions using
advanced artificial intelligence systems.

About Google

Software Development · 10,001+ employees · headquartered in Mountain View, CA