River AI Inc. Verified 2d ago
Member of Technical Staff, Hardware, Physical Design Engineer
Palo Alto, CAAll locationsPalo Alto, CAAustin, TX On-site
$200,000–$420,000 a yearPay$200,000–$420,000
TypeNot specified
Work settingOn-site
Verified listing
JobFig found this opening at its original source and checks that it remains available.
About the role
We are looking for exceptional physical design engineers to transform our high-performance architectural concepts into production-ready silicon. You will own the physical implementation flow from synthesis through tape-out, pushing the absolute limits of advanced foundry nodes to maximize PPA. You will take ownership of block-level and top-level physical design, collaborating tightly with RTL designers to close timing, electrical, and physical verification for our custom AI accelerator.
What you'll bring
- Bachelor’s degree in Electrical Engineering or Computer Engineering, and 5+ years practical industry experience working with advanced process nodes (7nm or below).
- Deep hands-on proficiency with industry-standard physical design, timing, and sign-off tools (e.g., Innovus, Fusion Compiler, PrimeTime, RedHawk).
- Proven track record running logic synthesis, integrating compiled memory macros, and managing multi-voltage design techniques using power intent specifications (UPF/CPF).
- Exceptional debugging skills with a first-principles approach to navigating complex trade-offs between congestion, timing slack, and power density in highly utilized designs.
- A highly collaborative mindset and a bias for action to push boundaries and co-design effectively with RTL and architecture teams.
- An extensive track record of delivering high-performance SoCs, CPUs, GPUs, or AI accelerators through multiple successful production tape-outs.
- Hands-on experience optimizing physical layouts for highly parallel compute structures, such as systolic arrays, large tensor execution units, or high-bandwidth memory (HBM) interfaces.
- Experience custom-scripting or extending EDA tools (using Tcl, Python, or specialized ML APIs) to automate physical design closure and build bespoke workflow pipelines.
Locations
Palo Alto, CAAustin, TX