Senior Principal Applied ML Engineer

Job summary

AT CADENCE, WE HIRE AND DEVELOP LEADERS AND INNOVATORS WHO WANT TO MAKE AN IMPACT ON THE WORLD OF TECHNOLOGY. Chips are at the center of today's tech-driven world. But how we design and verify them has not fundamentally changed in decades, while their complexity and specialization have skyrocketed due to increasing performance demands from AI.

Benefits

Qualifications

• BS with a minimum of 10 years of experience OR MS with a minimum of 7 years of experience OR PhD with a minimum of 5 years of experience
• Strong software engineering fundamentals, including design, refactoring, debugging, and testing of complex distributed systems.
• Demonstrated experience building production-quality systems.
• Understanding of large language models (LLMs) and practical considerations for deploying them in real-world systems (latency, cost, reliability, monitoring).
• Experience designing evaluation frameworks for AI systems, including benchmarking, regression testing, and failure analysis.
• skill level, competencies and work location.

Responsibilities

• Design and implement scalable infrastructure for AI agents operating within Cadence’s ChipStack SuperAgent ecosystem.
• Build robust evaluation frameworks to measure agent performance, reliability, and alignment with engineering workflows.
• Develop data pipelines, retrieval systems, and context-engineering strategies to support consistent and grounded agent behavior.
• Contribute to continuous integration, automated testing, and observability systems to ensure production-quality deployment of AI-enabled systems.
• Optimize system performance across latency, cost, reliability, and scalability dimensions.
• Required

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