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Positron

Memory-first AI inference silicon for LLMs

Senior ASIC Physical Design Engineer

Silicon & ASIC DesignUpdated on Nov 13
Full-time

About the Job

Requirements

  • 5–8 years of experience in physical design, spanning floorplanning through tapeout.
  • Experience contributing to one or more advanced-node tapeouts.
  • Strong proficiency in Innovus and/or ICC2 implementation flows.
  • Solid working knowledge of physical implementation, including floorplanning, clock tree synthesis, timing, and power closure.
  • Experience supporting signoff across timing, power, and related quality metrics.

Responsibilities

  • Support floorplanning, macro placement, and power planning across the AI accelerator designs.
  • Drive clock tree synthesis, place and route, and routing optimization through timing closure on assigned blocks.
  • Contribute to signal integrity, IR/EM closure, ECO implementation, and metal fill to deliver signoff-quality results.
  • Support tapeout signoff for physical implementation deliverables.
  • Contribute to methodology for power grids, power/ground tiles, and bump planning.
  • Assist in building congestion analysis and wire estimation approaches to support early floorplan decisions.
  • Support partitioning and hierarchical implementation strategies for complex, multi-block designs under guidance from senior/principal leads.
  • Execute Innovus-based implementation flows for assigned blocks.
  • Apply hands-on expertise across Innovus, ICC2, Tempus, PrimeTime, Voltus, RedHawk, and Calibre.
  • Drive closure across timing, power, area, congestion, DRC, LVS, EM, IR, and yield for owned blocks.
  • Partner closely with backend design services to align on implementation strategy and execution.
  • Participate in implementation quality reviews.
  • Apply AI-enabled techniques for automated QoR analysis, congestion prediction, routing prediction, and floorplan optimization.

Desired Qualifications

  • Experience with AI accelerator design.
  • Familiarity with large SRAM arrays.
  • Experience with SerDes and LPDDR interfaces.
  • Exposure to chiplet architectures and 2.5D advanced packaging.

About the Company

Positron

Memory-first AI inference silicon for LLMs

Positron develops memory-first AI inference silicon and systems to scale large-language-model serving. Its Atlas systems rely on commodity LPDDR5X memory rather than expensive HBM/CoWoS to boost bandwidth and capacity, enabling more efficient LLM deployment at hyperscale. The company’s next-generation Asimov silicon (tape-out planned for late 2026; production in 2027) pairs compute with very large memory per chip (roughly 288 GB to 2,304 GB) and is designed to be combined into Titan configurations (four to eight Asimov chips) for extremely large models and long context windows. Positron has already deployed Atlas systems in the cloud, including 50+ racks at Oracle Cloud Infrastructure and partnerships with Parasail, Jump Trading, and i3d.net. Its goal is to provide scalable, memory-rich AI inference hardware that lowers cost and increases throughput for serving large language models.

Company size
51-200
Company stage
Series C
Total funding
$1.2B
Headquarters
Reno, NV
Founded
2023

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