CAD Engineer

Location:

San Jose, CA (Onsite)

Duration:

6 Months

Pay Rate Range:

$90-$95/hr on W2

Job Description:

• Develop, maintain, and enhance EDA/CAD flows for ASIC design (RTL → GDSII lifecycle exposure preferred).
• Build automated flow checks for design validation, quality metrics, and regression monitoring.
• Create interactive dashboards and reporting tools to track design progress, QoR (Quality of Results), and key KPIs.
• Leverage AI/LLM-based tools to accelerate script development, debug flows, and generate insights from design data.
• Collaborate with design teams (RTL, PD, DV, DFT, STA) to identify gaps and implement automation solutions.
• Integrate tools and workflows across environments (Linux-based EDA setups, compute clusters, etc.).
• Analyze large datasets from design runs and provide actionable insights.
• Improve productivity by automating repetitive engineering tasks and optimizing workflows.
• Ensure robustness, scalability, and maintainability of developed solutions.

Requirements:

Required Qualifications:

• 5 years of experience in CAD/EDA development or related engineering roles.
• Strong programming skills in Python (mandatory) and scripting languages such as TCL, Bash, or Perl.
• Basic understanding of ASIC design flow (RTL, synthesis, place & route, STA, verification concepts).
• Experience with Linux/Unix environments and job scheduling systems.
• Hands-on experience building automation frameworks, validation checks, or internal tools.
• Familiarity with data visualization tools (e.g., dashboards using Python, web frameworks, or BI tools).
• Strong problem-solving skills and ability to work in a fast-paced environment.

Preferred Qualifications:

• Experience with EDA tools (e.g., Synopsys, Cadence, Siemens/Mentor toolchains).
• Exposure to design data formats (logs, reports, timing/power data, etc.).
• Experience with AI-assisted coding tools (e.g., GitHub Copilot, ChatGPT, internal LLMs) and prompt engineering.
• Knowledge of data engineering concepts (data pipelines, parsing large datasets, analytics).
• Familiarity with cloud or distributed compute environments.
• Experience building web-based dashboards (Flask, Django, React, etc.).