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Artificial Intelligence, Semiconductors

Chip Design Engineer

Palo Alto, CAOnsiteFull TimePosted 1 month ago

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Required skills

  • tapeout
  • advanced node
  • PPA-critical
  • EM/IR signoff
  • DRC/LVS closure
  • ECOs
  • hierarchical flows

Nice to have

  • Masters
  • VLSI
  • physical design
  • EDA/CAD algorithms
  • high-performance compute silicon
  • ML accelerators

Role summary

Ricursive Intelligence, a frontier AI lab backed by significant funding, is seeking a Chip Design Engineer to revolutionize chip development by integrating AI with hardware. This role involves hands-on contribution across the entire chip design flow, from synthesis to tapeout, with a focus on closing complex, PPA-critical blocks in advanced nodes. The engineer will also partner on chip design infrastructure and automation. The ideal candidate possesses 5+ years of physical design experience, fluency in production implementation stacks, and a track record of successful chip tapeouts. Preferred qualifications include advanced degrees and expertise in high-performance compute silicon or AI for chip design.

Ricursive Intelligence is a frontier AI lab building self-improving systems, starting with chip design. We are reinventing chip development and closing the loop between AI and the hardware that fuels it, recursively accelerating the path to artificial superintelligence. Backed by $335M from Sequoia, Lightspeed, DST, and NVIDIA Ventures, we are a growing, fast-paced team where every hire shapes the work.

The company has unmatched talent density, including IMO, IPhO, and IOAA gold medalists, pioneers who made prior breakthroughs in chip design: AlphaChip (Nature 2021), ePlace (DAC Best Paper Nominee 2014), RL-CCD (DAC Best Paper 2023), INSTA (DAC Best Paper 2025), and C3PO (ASP-DAC Best Paper 2026), chip leads for Apple Silicon (multiple generations of iPhone and iPad) and Google (TPU, OpenTitan), and top researchers and engineers from Anthropic, Google DeepMind, Stanford, and MIT.

ABOUT THE ROLE

We are hiring an engineer who deeply understands every step of the flow, from synthesis through tapeout, and who has personally fought complex blocks to closure at an advanced node. Your expertise will be used to define and implement the design of self-improving systems that you will then use to build real silicon.

WHAT YOU WILL DO

  • Own designs for synthesis, DFT insertion, floorplanning, PDN design, placement, CTS, routing, and all electrical, timing, and physical signoff.

  • Own timing, power, and physical closure of the most complex, PPA-critical blocks in advanced nodes, driving multi-mode multi-corner timing convergence, EM/IR signoff, and DRC/LVS closure through final ECOs and tapeout.

  • Own chip design infrastructure and automation, optimization techniques and goals, and design improvement strategies.

MINIMUM QUALIFICATIONS

  • BS in Electrical Engineering, Computer Engineering, Computer Science, or a closely related technical field.

  • 5+ years of hands-on physical design experience spanning every step of the flow (synthesis, floorplanning, PDN, placement, CTS, routing, STA, extraction, power/EM/IR analysis, physical verification, LEC, and ECO), including experience architecting hierarchical flows both top-down and bottom-up.

  • Day-one fluency in at least one production implementation and signoff stack with chip design tools and strong Tcl and Python scripting.

  • Track record of successful chip design and tapeout: owned closure of complex blocks, subsystems, or full chips through complete signoff in advanced technology nodes, on silicon that taped out and shipped to production.

  • Ability to develop and debug chip design flows, tools, and infrastructure to achieve challenging design requirements for quality and schedule.

PREFERRED QUALIFICATIONS

  • Masters or PhD in EE, CE, CS, or a related field, with a focus on VLSI, physical design, or EDA/CAD algorithms.

  • Deep expertise in high-performance compute silicon (e.g., ML accelerators, CPUs, GPUs, or large SoCs), including multi-voltage domain (UPF) design and 2.5D/3D integration with bump/RDL planning.

  • Publications at major conferences (e.g., DAC, ICCAD, ISPD, DATE) demonstrating research strength in physical design or AI for chip design.

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