10 часов назад
Physical Design Engineer (AI Hardware)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Physical Design Engineer (AI Hardware): Driving RTL-to-GDSII implementation and high-performance silicon design closure for next-generation AI hardware with an accent on floorplanning, timing closure, power integrity, and physical verification. Focus on optimizing PPA at 3nm and below, analyzing signal integrity and electromigration, and developing AI/ML-based automation for EDA workflows.
Location: Bangalore, India
Company
develops advanced AI hardware and software systems for edge-to-cloud computing, using in-memory computing technology for high-efficiency applications in power-, energy-, and space-constrained environments.
What you will do
- Own RTL-to-GDSII implementation, including floorplanning, placement, clock tree synthesis, routing, and physical verification.
- Drive PPA closure for advanced process nodes at 3nm and below.
- Perform static timing analysis and timing closure, including signal integrity, crosstalk, and CPPR optimization.
- Analyze static and dynamic IR drop and perform electromigration checks for robust power delivery.
- Develop and integrate AI/ML-based automation scripts to optimize physical design flows and reduce turnaround time.
Requirements
- B.Tech or M.Tech in Electrical or Electronics Engineering from a top-tier university.
- 2–4 years of hands-on physical design experience in the semiconductor industry.
- Expert proficiency with industry-standard physical design tools, preferably Innovus.
- Strong knowledge of MCMM closure, low-power design techniques using UPF/CPF, and physical verification.
- Ability to take complete ownership of design blocks and solve complex silicon challenges under tight deadlines.
Nice to have
- Proficiency in Python or Tcl.
- Experience applying AI/ML models to EDA tool automation or predictive PPA analysis.
Culture & Benefits
- Work in a fast-paced startup environment focused on next-generation silicon and AI-driven automation.
- Contribute to high-performance computing technology for edge-to-cloud applications.
- Take ownership of challenging physical design blocks and advanced semiconductor workflows.
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