- Define the AI architecture strategy spanning data pipelines model selection and deployment for semiconductor design use cases
- Architect and prototype AIML solutions that augment backend design STA DFT and physical verification flows eg PPA optimization automated DFT insertion logreport analysis predictive timing closure
- Integrate LLMs and ML models into existing EDA toolchains Innovus Tempus PrimeTime Calibre etc and LinuxTCLPython scripting environments
- Architect agentic AI workflows agents that plan execute and iterate across multistep design tasks debug triage ECO loop automation constraint generation regression analysis with appropriate humanintheloop checkpoints
- Design multiagent systems that orchestrate specialized agents across the RTLtoGDSII flow integrating tool calls to EDA engines scripts and internal knowledge bases
- Build robust agent infrastructure toolfunctioncalling interfaces context and memory management state handling and guardrails for reliability in engineeringcritical applications
- Evaluate and benchmark foundation models finetuning approaches RAG pipelines and agent orchestration patterns
- Establish an agent control plane policy approval gates observability and audit trails before autonomous agents touch production systems
- Partner with delivery teams and clients to translate AI capabilities into productized service offerings
- Establish MLOps practices model governance and scalable infrastructure onpremcloudhybrid
- Mentor engineers on AIML adoption and build the technical foundation for an AI Center of Excellence
Experience (years) : 10+ years
Education Qualification
BTECH/MTECH in Electrical/Electronics/Computer Science Engineering or Equivalent
Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.