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Cadence Design Systems

Develops EDA software, IP, verification tools

Applied ML Director – Technical Team Lead

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeSan Jose, CA, USAIn-person

About the Job

Requirements

  • A Master of Science or PhD in Computer Science, Computer Engineering, or a related technical field.
  • At least 3 years of direct engineering management or formal technical lead experience, including mentoring engineers and delivering complex projects.
  • At least 7 years of hands-on software engineering and machine learning experience, with deep expertise in designing, refactoring, debugging, and testing distributed systems, and the ability to write production-quality code.
  • Deep understanding of large language models and the practical considerations of deploying them in production, including latency, cost, reliability, monitoring, and failure analysis.
  • Experience designing rigorous AI-system evaluation frameworks, including benchmarking and regression testing.

Responsibilities

  • Manage and grow a high-performing team of machine learning and software engineers, fostering technical excellence, continuous learning, and rapid execution.
  • Drive the technical vision and contribute actively to the codebase; design, implement, and review scalable infrastructure for AI agents within the ChipStack SuperAgent ecosystem.
  • Guide development of evaluation frameworks, data pipelines, retrieval systems, and context-engineering strategies to support consistent, grounded, and aligned agent behavior.
  • Oversee continuous integration, automated testing, and observability systems; make architectural decisions to optimize system performance for latency, cost, reliability, and scalability.
  • Partner with product management, research, and core engineering teams to align the AI roadmap with broader EDA platform goals.

Desired Qualifications

  • Hands-on experience with agent architecture, including reason–act loops, planning and self-correction patterns, tool or function calling, persistent memory systems, and structured outputs.
  • Familiarity with frontier large language models and trade-offs across model families; practical experience with prompt engineering, context management, and model-alignment techniques.
  • Deep understanding of retrieval-augmented generation pipelines, embeddings, indexing strategies, chunking methodologies, and grounding techniques.
  • Experience building logging, tracing, monitoring, and evaluation systems tailored for machine-learning and AI applications.
  • Strong interest in semiconductor design, electronic design automation workflows, and high-performance computing environments; prior electronic design automation experience is a plus but is not required.

About the Company

Cadence Design Systems

Develops EDA software, IP, verification tools

Cadence Design Systems supplies software, hardware, and IP for electronic design automation (EDA) to help customers create advanced semiconductor chips and electronic systems. Its tools handle system design, verification, digital and analog IC design, and custom flows, while IP such as Tensilica processors and DSP cores can be licensed for integration into customer products. The offerings are delivered as software licenses with maintenance and support, plus IP licensing and occasional hardware-accelerated options. The company differentiates itself with a broad, end-to-end EDA portfolio and close collaboration with industry leaders to streamline the path from concept to silicon, aiming to help customers bring sophisticated silicon and electronics to market faster with lower risk and higher productivity.

Company size
10,001+
Company stage
IPO
Headquarters
San Jose, CA
Founded
1988

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