Applied ML Director (Technical Team Lead)
About The Position
Cadence Design Systems is the leading provider of design automation tools for electronic and intelligent systems design. As the Applied ML Director for the ChipStack SuperAgent Team, you will lead a highly technical group of ML and software engineers responsible for designing, implementing, and evaluating AI agents that enhance productivity across the semiconductor design lifecycle. This is a true "player-coach" role. You will act as the technical backbone of the team—deeply hands-on with architecture, system design, and coding—while concurrently managing, mentoring, and scaling the engineering team. You will drive the technical roadmap for our agent infrastructure, evaluation systems, and production-grade AI capabilities integrated within Cadence’s EDA ecosystem. The ideal candidate pairs seasoned engineering leadership with practical, in-the-weeds experience building scalable ML systems and agentic workflows.
Requirements
- Education: MS or PhD in Computer Science, Computer Engineering, or a related technical field.
- Leadership Experience: 3+ years of direct engineering management or formal technical lead experience, with a proven track record of successfully mentoring engineers and delivering complex projects.
- Engineering Fundamentals: 7+ years of hands-on software engineering and ML experience. You must possess deep expertise in design, refactoring, debugging, and testing distributed systems—and you should still be comfortable writing production-quality code today.
- LLM Expertise: Deep understanding of large language models (LLMs) and the practical realities of deploying them in production (latency, cost, reliability, monitoring, and failure analysis).
- System Evaluation: Experience designing rigorous evaluation frameworks for AI systems, including benchmarking and regression testing.
Nice To Haves
- Agent Architecture: Hands-on experience with reason–act loops, planning/self-correction patterns, tool/function calling, persistent memory systems, and structured outputs.
- LLM Engineering: Familiarity with frontier LLMs and trade-offs across model families; practical experience with prompt engineering, context management, and model alignment techniques.
- Retrieval & Data Systems: Deep understanding of RAG pipelines, embeddings, indexing strategies, chunking methodologies, and grounding techniques.
- Infrastructure & Observability: Experience building logging, tracing, monitoring, and evaluation systems specifically tailored for ML/AI applications.
- Domain Interest: A strong interest in semiconductor design, EDA workflows, and high-performance computing environments (prior EDA experience is a plus, but not required).
Responsibilities
- Lead & Mentor: Manage and grow a high-performing team of ML and software engineers. Foster a culture of technical excellence, continuous learning, and rapid execution.
- Hands-On Technical Leadership: Drive the technical vision and actively contribute to the codebase. Design, implement, and review scalable infrastructure for AI agents within the ChipStack SuperAgent ecosystem.
- Architect Production AI: Guide the development of robust evaluation frameworks, data pipelines, retrieval systems (RAG), and context-engineering strategies to ensure consistent, grounded, and aligned agent behavior.
- Operational Excellence: Oversee continuous integration, automated testing, and observability systems. Make high-level architectural decisions to optimize system performance across latency, cost, reliability, and scalability.
- Cross-Functional Collaboration: Partner with product management, research, and core engineering teams to align the AI roadmap with overarching EDA platform goals.
Benefits
- paid vacation and paid holidays
- 401(k) plan with employer match
- employee stock purchase plan
- a variety of medical, dental and vision plan options
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What This Job Offers
Job Type
Full-time
Career Level
Manager
