Hiring: Applied ML Director (Technical Team Lead) Company: Cadence Location: San Jose, CA Job Posted Time: 2026-09-03 10:20:17 Target Skills & Keywords : Data Pipeline, Design System, EDA, LLM, RAG, Systems Design About the job 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. •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. Required Skills: •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. Qualifications: •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. •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). •Challenge the status quo: We are innovators who challenge industry norms and push forward our vision of how silicon should be built. Compensation: •$178,500 - $331,500 / year •You may also be eligible to receive incentive compensation: bonus, equity, and benefits Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!