Applied AI Engineer - DFT Methodology
Hybrid · Bengaluru, Karnataka, India
Job Summary
Architect end-to-end generative AI solutions for DFX and VLSI problem statements, focusing on LLMs, RAGs, and Agentic AI workflows; deploy predictive ML models for Silicon Lifecycle Management of NVIDIA chips; collaborate with VLSI/DFX teams to tailor AI solutions; guide data collection, storage, and management for next-generation AI use cases; mentor junior engineers on test designs and trade-offs including cost and quality; require BSEE/MSEE with 2+ years in DFT, VLSI, and Applied ML; proficiency in Perl, Python, C++, or TCL.
Required Qualifications
- BSEE or MSEE from reputed institutions with 2+ years of experience in DFT, VLSI & Applied Machine Learning
- Experience in Applied ML solutions for chip design problems
- Significant experience in deploying generative AI solutions for engineering use cases
- Good understanding of fundamental DFT & VLSI concepts - ATPG, scan, RTL & clocks design, STA, place-n-route and power
- Experience in application of AI for EDA-related problem-solving is a plus
- Strong programming and scripting skills in Perl, Python, C++ or TCL desired
- Strong organization and time management skills to work in a fast-pace multi-task environment
- Self-motivated, independent, ability to work independently with minimal day-to-day direction
- Outstanding written and oral communication skills with the curiosity to work on rare challenges
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