Senior Design Verification Engineer, AI/ML, Google Cloud

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
  
• 10 years of experience in Electronic Design Automation (EDA) tools and IP/chip design and verification methodologies.
  
• Experience in establishing and qualifying SoC design flows from an EDA reference flow and addressing product specific design/methodology requirements.
  
• Experience in solving verification issues with AI/ML algorithms and techniques.
  
• Experience with Verilog, System Verilog, Register-Transfer Level (RTL) design, simulation, Universal Verification Methodology (UVM) and static checks, clock and reset domain crossing.
  

Preferred qualifications:

• Experience with cloud-based Machine Learning (ML) frameworks and tools.
  
• Experience in developing AI/ML models for verification tasks, such as coverage analysis or bug prediction.
  
• Experience in formal verification methodologies.
  
• Familiarity with hardware acceleration platforms (e.g., GPUs, TPUs).
  
• Excellent problem-solving and investigative skills.
  
• Excellent communication and teamwork skills.
  

About the job

Be part of a diverse team that pushes boundaries, developing custom silicon solutions that power the future of Google's direct-to-consumer products. From Pixel phones to Nest devices and Fitbit wearables, you'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration.

As an Executive Design Verification Engineer specializing in AI/ML methodology, you will be transforming the verification landscape for cutting-edge hardware designs. You will play a pivotal role in integrating AI/ML techniques into pre-silicon and post-silicon verification processes, enhancing their efficiency, effectiveness, and reliability. You will develop innovative solutions that automate repetitive tasks, uncover hidden design flaws, and optimize verification strategies, ultimately leading to faster time-to-market and higher quality products. You will collaborate with cross-functional teams and stay up-to-date on the latest advancements in AI/ML. You will contribute to shaping the future of hardware verification at Google, ensuring the company's products meet the highest standards of quality and performance.

Behind everything our users see online is the architecture built by the Technical Infrastructure team to keep it running. From developing and maintaining our data centers to building the next generation of Google platforms, we make Google's product portfolio possible. We're proud to be our engineers' engineers and love voiding warranties by taking things apart so we can rebuild them. We keep our networks up and running, ensuring our users have the best and fastest experience possible.

Be part of a diverse team that pushes boundaries, developing custom silicon solutions that power the future of Google's direct-to-consumer products. From Pixel phones to Nest devices and Fitbit wearables, you'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration.

Responsibilities

• Analyze verification data to identify trends, patterns, and areas for improvement, utilizing AI/ML to gain valuable insights and optimize verification strategies.
  
• Work closely with design, architecture, and software teams to ensure seamless integration of AI/ML driven verification solutions into the overall hardware development process.
  
• Research and explore new AI/ML algorithms and techniques applicable to various verification tasks, such as test generation, coverage analysis, bug triaging, and root cause analysis.
  
• Work closely with Google DeepMind team on AI models (e.g., large language model (LLM), Gemini and other Machine Learning tools). Collaborate with verification teams to enhance existing verification methodologies by incorporating AI/ML techniques, ensuring a more comprehensive, and efficient verification process.
• Be involved in accelerating design convergence using the aforementioned methodology improvements.

Work closely with Google DeepMind team on AI models (e.g., large language model (LLM), Gemini and other Machine Learning tools). Collaborate with verification teams to enhance existing verification methodologies by incorporating AI/ML techniques, ensuring a more comprehensive, and efficient verification process.Work closely with Google DeepMind team on AI models (e.g., large language model (LLM), Gemini and other Machine Learning tools). Collaborate with verification teams to enhance existing verification methodologies by incorporating AI/ML techniques, ensuring a more comprehensive, and efficient verification process.Be involved in accelerating design convergence using the aforementioned methodology improvements.Be involved in accelerating design convergence using the aforementioned methodology improvements.