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AI / ML DFT Project Lead

AMD· Engineering
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Santa Clara, CA$232kFull-timePosted 3w ago

About the role

AI/ML Project Lead within Central DFX (CDFX) focusing on designing and deploying AI-enabled capabilities to improve DFT/DFD design, verification, and automation for AMD's ASIC flows.

Responsibilities

  • Lead the strategy, roadmap and execution of AI/ML and agentic AI initiatives for DFT and DFD design, methodology, verification and debug workflows.
  • Integrate AI agents and services with DFX design flows, EDA tools, repositories, specifications, regression systems and engineering data sources through secure, maintainable interfaces.
  • Develop AI-enabled expert systems, predictive models and intelligent automation to address DFT challenges across IP, subsystem and SoC design environments.
  • Maintain awareness of advancements in AI/ML, agentic systems and semiconductor design automation, and evaluate their relevance to AMD DFX needs.
  • Identify and prioritize use cases based on measurable engineering value, technical feasibility, data readiness, deployment risk and opportunities for reuse across teams.
  • Architect agentic workflows that combine large language models, domain knowledge, retrieval, tools, automation and human-in-the-loop controls to support complex engineering tasks.
  • Establish evaluation methods, quality gates, guardrails, traceability and fallback mechanisms appropriate for production engineering workflows.
  • Lead model and application deployment, monitoring, incident response, maintenance and continuous improvement using MLOps, DevOps and software lifecycle practices.
  • Drive scalable DFT implementation and verification automation using Python, Perl, Tcl and shell scripting within complex ASIC design environments.
  • Coordinate cross-functional project plans, dependencies, risks, milestones and technical decisions, and communicate progress clearly to engineering and leadership stakeholders.
  • Mentor engineers, promote reusable architecture and coding practices, and build organizational capability in responsible AI-assisted engineering.

Qualifications

  • Extensive experience in DFT and/or DFD architecture, design, implementation, verification or methodology for high-performance SoCs and IP.
  • Demonstrated technical leadership of complex, cross-team engineering initiatives from definition through production adoption.
  • Hands-on experience developing and deploying AI/ML applications in production or enterprise engineering environments.
  • Familiar with agentic AI systems design, including tool use, multi-agent/subagent systems, Model Context Protocol (MCP), workflow orchestration, Retrieval-Augmented Generation (RAG), structured outputs, evaluation and human oversight.
  • Experience designing agentic AI systems, including tool use, workflow orchestration, retrieval-augmented generation, structured outputs, evaluation and human oversight.
  • Strong Python development skills and experience with relevant AI/ML frameworks and libraries. Familiarity with scikit-learn, PyTorch, TensorFlow or equivalent technologies is desirable.
  • Experience with software engineering and deployment practices such as source control, code review, automated testing, CI/CD, APIs, containers and observability.
  • Knowledge of MLOps and data lifecycle practices, including data quality, model evaluation, versioning, monitoring and reproducibility.
  • Proficiency with one or more ASIC/EDA automation languages, including Perl, Tcl and shell scripting.
  • Strong foundation in digital logic, VLSI design and the interactions among test, power, timing, area, physical design and verification constraints.
  • Proven ability to influence technical direction across organizational boundaries and convert ambiguous problems into executable project plans.

Skills

Required:AI/ML application developmentAgentic AI systems designPython developmentSoftware engineering practicesMLOps / data lifecycleASIC/EDA automation languages

Benefits

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Last updated Oct 22, 2026. Interested? Apply on the company site.
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