Senior Physical Design Methodology Engineer, Ppa Fusion Compiler

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA +2

Senior Physical Design Methodology Engineer focused on developing and implementing ML-based solutions to improve Power, Performance, and Area (PPA) for graphics processors and SOCs. This role involves developing efficient physical design methodologies, formulating ML-based solutions, and participating in the full chip design flow.

What you'd actually do

  1. Developing Efficient physical design methodologies for implementation of graphics processors and SOCs.
  2. Key responsibility includes developing unique and creative solutions to the state-of-the-art physical design problems to improve PPA
  3. Knowledge and experience to formulate and develop with ML-based solutions
  4. Participate in developing flow and tool methodologies for P&R, timing analysis and closure, convergence in IR/Signal-EM, power and noise analysis and back-end verification across multiple projects along with chip floorplan, power and clock distribution, chip assembly.
  5. Data based analysis and algorithmic solutions for PPA check and improvement.

Skills

Required

  • MS in Electrical, Computer Engineering, computer science (or equivalent experience)
  • 10+ years’ experience in Physical Design Engineering
  • ML based solution development experience
  • Proven implementation of ML-based solutions
  • Familiar with aspects of chip design including Floor planning, Clock and Power distribution, Place and Route, Integration and Verification.
  • Staring knowledge of Physical design with convergence in timing/EM/IR with best PPA
  • Strong background with hierarchical design approach, top-down design, budgeting, timing and physical convergence.
  • Familiar with various process related design issues including Design for Yield and Manufacturability, EM and IR closure and thermal management.
  • Solid understanding of standard industry PnR tools and analysis tools
  • Capable of extensive scripting to check and improve PPA

What the JD emphasized

  • ML-based solutions
  • 10+ years’ experience in Physical Design Engineering with ML based solution development experience
  • Proven implementation of ML-based solutions

Other signals

  • ML-based solutions
  • physical design methodologies
  • PPA improvement