Description

You will integrate machine learning technologies into hardware verification workflows to drive data-driven decision making and improve efficiency.

Responsibilities

• Embed ML4V technologies into testbenches and production environments to optimize workflows and test generation.
• Collaborate with data scientists to extract testbench data for improving machine learning models.
• Debug ML4V issues in partnership with Engineering and DevOps teams to ensure service continuity.
• Evaluate emerging ML technologies from internal teams and EDA partners.
• Report on user experience and project requirements to inform the ML4V roadmap.

Required Skills

• 5+ years of experience in hardware verification.
• Proficiency in System Verilog and UVM.
• Experience developing coverage-driven constrained-random verification environments.
• Experience managing all stages of the verification lifecycle for complex IP.
• Proficiency in Python or other interpreted scripting languages.
• Experience with shell scripting.

Preferred Skills

• Experience with C/C++.
• Proficiency with EDA simulation, debug, and coverage tools in batch workflows.
• Understanding of machine-readable formats like JSON.

Key Skills

Education

Any Graduate