Role : Director of AI/ML Engineering (EDA & Semiconductor Design)

Job Description :

In this role, you will lead the definition and execution of AI/ML-driven initiatives, drive adoption of ML/AI across frontend and backend design and development flows across the company, enable next-generation intelligent design automation capabilities, and collaborate with cross-functional leaders to integrate AI into engineering productivity, automation, and decision-making processes.

Job Responsibilities :

- Define and own the AI/ML strategy for Engineering groups software and design flows

- Lead the transformation of semiconductor design workflows by deploying AI-driven (agentic) solutions across Frontend (modelling, synthesis, optimization) and Backend (place-and-route, timing closure, physical optimization)

- Drive end-to-end integration of AI into engineering toolchains

- Establish scalable frameworks for :

1. Data collection, labelling, and pipeline management

2. Model training/fine tuning, validation, and deployment

- Lead cross-functional collaboration with :

1. EDA, design, architecture, and platform teams

2. External vendors and partners as needed

- Build and grow a high-performance engineering team

- Define KPIs to measure productivity gains, quality improvements, and ROI from AI initiatives

- Ensure alignment with enterprise AI programs and governance frameworks

- Drive continuous innovation and adoption of emerging AI/ML technologies in semiconductor workflows

Qualifications :

- MTech/BTech in EE/CS with 20+ years of software development experience and 10+ years of engineering management experience (including leading managers or large teams)

- 7+ years in semiconductor and/or EDA industry

- Proven experience in Applying ML/AI to real-world engineering or automation problems

- Proven experience building and scaling AI/ML platforms leveraging technologies such as LangChain, vector databases, and RAG-based architectures

- Deep understanding of LLM ecosystems, including embeddings, knowledge retrieval, and integration of AI agents into production workflows

- Strong understanding of software architecture, distributed systems, Data pipelines and ML workflows

- Demonstrated ability to Lead cross-functional initiatives and translate business/engineering needs into technical solutions

- Should have exposure to quality processes for project execution, delivery, and working with multiple teams across geos

- Strong communication skills for executive-level engagement

- Preferred Hands-on experience with EDA tools, chip design flows, or semiconductor development lifecycle

- Prior Hands-on experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, or similar) is a plus

- Prior experience building AI-driven solutions for Design optimization and Automation/ productivity improvement is preferred

- Familiarity with Cloud platforms and scalable compute infrastructure and Data-driven decision systems is preferred