11 часов назад
Senior Physical Design Engineer (AI Hardware)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior Physical Design Engineer (AI Hardware): Leading block-level RTL-to-GDSII implementation for advanced AI silicon with an accent on PPA optimization, timing closure, physical verification, and automation. Focus on developing custom optimization strategies, resolving DRC/LVS, IR drop, and timing violations, and building Tcl/Python tooling for efficient physical design flows.
Location: Bangalore, India — hybrid
Company
develops advanced AI hardware and software systems for edge-to-cloud computing using in-memory computing technology for power-, energy-, and space-constrained applications.
What you will do
- Own physical implementation of complex blocks from synthesis and floor-planning through clock-tree synthesis, routing, and sign-off.
- Analyze timing paths, power profiles, and congestion to develop customized PPA optimization strategies.
- Use Tcl and Python to automate repetitive tasks, parse data, and improve the physical design environment.
- Converge partitions from RTL to clean GDSII while resolving DRC/LVS, ERC, IR drop, and timing violations.
- Collaborate with RTL and DFT teams to introduce physical constraints early and improve routing and timing outcomes.
Requirements
- 4–7 years of physical design experience, including 2–3 successful tape-outs.
- Hands-on experience with Cadence Innovus and Tempus.
- Proficiency in Tcl for tool control and Python for data parsing and flow automation.
- Experience improving power, performance, and area through floor-planning and placement tuning.
- Strong debugging skills in static timing analysis, EM/IR, and physical verification including DRC, LVS, and ERC.
- Ability to work independently, investigate root causes through logs and data, and challenge inefficient processes.
Culture & Benefits
- Work in an advanced silicon team focused on next-generation AI computing technology.
- Operate with a high degree of independence and ownership over complex partitions.
- Collaborate across physical design, RTL, and DFT disciplines.
- Apply a curiosity-driven, analytical approach to improving tools and design flows.
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