Applied ML Director, AI Agents for EDA
Overview
You will lead the ChipStack SuperAgent team at Cadence, owning the technical roadmap and delivery of production-grade AI agents that accelerate semiconductor design. With 7+ years in ML engineering and 3+ years leading technical teams, you will balance hands-on coding with team management, driving architecture, evaluation systems, and integration across EDA platforms like Xcelium, Jasper, and Palladium. You will partner with product and research to align AI priorities, and your work will directly impact how chips are designed and verified in an AI-driven world.
What You'll Do7
- 1Lead and mentor a team of ML and software engineers, setting technical direction and fostering a culture of ownership and quality.
- 2Design and implement scalable agent infrastructure, including RAG pipelines, LLM orchestration, and tool-calling systems.
- 3Drive the development of evaluation frameworks that measure agent accuracy, latency, and reliability across production scenarios.
- 4Architect RAG retrieval systems with embeddings, indexing, and chunking strategies to ensure grounded responses.
- 5Oversee automated testing, CI/CD pipelines, and observability for AI systems, including logging and tracing.
- 6Debug and optimize system performance across latency, cost, and reliability, making high-impact architectural decisions.
- 7Collaborate with product management, research, and core engineering to integrate AI capabilities into EDA workflows.
Requirements9
- 1MS or PhD in Computer Science, Computer Engineering, or related field.
- 23+ years of engineering management or formal technical lead experience, with a proven record of mentoring engineers.
- 37+ years hands-on software engineering and ML experience, building distributed systems with production-quality code.
- 4Deep expertise in LLM deployment, including latency tuning, cost management, and failure analysis.
- 5Experience designing evaluation frameworks for AI systems, with benchmark and regression testing.
- 6Hands-on experience with RAG, including embeddings, index strategies, and grounding techniques.
- 7Knowledge of reason-act loops, planning, and tool use in agent architectures.
- 8Proven ability to build monitoring and tracing systems for ML applications.
- 9Interest in semiconductor design and EDA workflows; prior experience is a plus.
Salary Insight
$178 - $332k per year
Location
Required Skills
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