Machine Learning Engineer, Design Verification, Silicon
- linkCopy link
- emailEmail a friend
Minimum qualifications:
- Bachelor's degree in Computer Engineering, Electrical Engineering, Computer Science, or related field, or equivalent practical experience.
- 5 years of experience with ML/AI frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn).
- Experience with hardware description languages (e.g., Verilog, SystemVerilog, VHDL).
- Experience with applying ML/AI techniques.
Preferred qualifications:
- Experience with ML/AI applications in hardware design, verification and Low Power (e.g., formal verification with ML, coverage closure with ML).
- Experience with verification methodologies (UVM, OVM).
- Experience in data preprocessing and feature engineering, hardware architecture and microarchitecture.
- Experience with simulation tools (e.g., Synopsys VCS, Cadence Xcelium, Mentor Questa).
- Excellent programming skills in Python or C++.
About the job
Google's mission is to organize the world's information and make it universally accessible and useful. Our team combines the best of Google AI, Software, and Hardware to create radically helpful experiences. We research, design, and develop new technologies and hardware to make computing faster, seamless, and more powerful. We aim to make people's lives better through technology.
Responsibilities
- Research, design, and implement ML/AI algorithms techniques for various verification tasks, including test case generation, coverage analysis, bug prediction, and performance optimization. Develop and maintain tools and scripts for data collection, preprocessing, model training, and evaluation.
- Analyze large datasets of simulation results, logs, and other verification data to identify patterns and trends.
- Build and train ML models for various verification applications, such as anomaly detection, pattern recognition, and prediction.
- Evaluate model performance and iterate to improve accuracy and efficiency.
- Participate in verification planning and develop test plans that incorporate ML/AI-driven techniques. Execute verification tests and analyze results to identify bugs and coverage gaps. Develop and maintain verification tools and scripts to automate verification tasks.
Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google's Applicant and Candidate Privacy Policy.
Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy, Know your rights: workplace discrimination is illegal, Belonging at Google, and How we hire.
If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form.
Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.
To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes.