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