BS or MS in Electrical Engineering, Computer Science, or equivalent experience
2+ years in CAD/EDA flow engineering or related semiconductor role
Strong programming skills in Python; familiarity with shell, Tcl, or Perl
Hands-on experience applying machine learning in engineering contexts
Solid understanding of major EDA workflow domains like STA, DRC/LVS, or physical layout
Experience with large-scale operational data from EDA logs and reports
Responsibilities
Identify and prioritize AI/ML opportunities in chip design and verification workflows
Build and maintain data pipelines for extracting and analyzing EDA tool signals
Develop ML models and analytics to enhance efficiency in STA and DRC/LVS areas
Integrate AI solutions into existing CAD infrastructure and frameworks
Collaborate with EDA vendors for tool support and evaluation of solutions
Benefits
Collaborative work environment with design teams and stakeholders
Opportunity to work with cutting-edge AI-driven solutions
Involvement in impactful projects that facilitate substantial workflow improvements
Exposure to a wide range of EDA tools and methodologies
Scope for professional growth in semiconductor and machine learning domains
Full Job Description
Description
Position Overview:
Work closely with design teams and CAD/EDA stakeholders to identify workflow bottlenecks across the chip development lifecycle-such as DRC/CDC/STA debug, regression triage, PPA convergence, and ECO iteration. This role focuses on building scalable data pipelines and models, and integrating AI-driven solutions into production CAD and verification flows.
Responsibilities:
Identify and prioritize high-impact opportunities to apply AI/ML to chip design and verification workflows, spanning RTL-to-GDS, signoff, debug, and regression
Build and maintain data pipelines to extract, normalize, and analyze signals from EDA tool logs, reports, run artifacts, and design metadata (e.g., timing reports, violations, coverage, failures)
Develop ML models, heuristics, and analytics to improve efficiency and quality in areas such as STA, DRC/LVS, ECO optimization, and debug acceleration
Integrate AI solutions into existing CAD infrastructure, including automation systems, regression frameworks, job schedulers, and design databases
Collaborate with EDA vendors as needed for tool enablement, feature requests, debugging, and evaluation of vendor solutions versus internal implementations
Requirements:
BS or MS in Electrical Engineering, Computer Science, or equivalent industry experience
2+ years of experience in CAD/EDA flow engineering, design automation, or a related semiconductor workflow role
Strong programming skills, with Python required; experience with shell, Tcl, or Perl as needed
Hands-on experience applying machine learning to real-world engineering problems
Solid understanding of at least one major EDA workflow domain (e.g., place & route, physical layout, DRC/LVS, STA, power, CDC, DFT, simulation/regressions)
Experience working with large-scale, noisy operational data (EDA logs and reports) and building robust automation around it
Annual base salary for this role in California, US is expected to be between $110,000 - $145,000. Actual pay will be determined by several factors such as relevant skills and experience, and the pay of employees in a similar role.
About OmniVision Technologies
OmniVision Technologies, Inc. is a leading developer of advanced digital imaging solutions. The company designs and manufactures image sensors and related technologies for a range of applications, including mobile devices, automotive, security, and medical imaging. OmniVision's products are used by leading manufacturers around the world, and the company is known for its innovation and expertise in the field of digital imaging. OmniVision was founded in 1995 and is headquartered in Santa Clara, California.
