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AI/ML Physical Design Flow Engineer

Tenstorrent · Hybrid

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Last seen by MeritLog September 12, 2026Source: GreenhouseSource version: greenhouse-job-board-v1

Source: the employer's Greenhouse job board. Open the original listing for current details. Availability is not verified for this retained page.

Job details

Work model
Hybrid
Salary
Not listed by source
Location
Austin, Texas, United States; Fort Collins, Colorado, United States; Santa Clara, California, United States

What the role asks for

What they're asking for

  • BS in Electrical or Computer Engineering (or equivalent experience) with 5+ years in Physical Design CAD methodology at advanced nodes.Education
  • Proven track record improving PPA and/or runtime on high-performance, low-power taped-out designs.Skill
  • Hands-on with industry-standard EDA tools (e.g., Fusion Compiler) across synthesis, P&R, STA, signoff, and hierarchical flows.Skill
  • Strong Python/Tcl and data skills, with interest or experience in ML frameworks (PyTorch, TensorFlow), and the ability to drive complex projects independently.Skill
  • Lead and contribute to cross-functional efforts solving complex physical design challenges across IPs, projects, and advanced technology nodes.Skill
  • Develop and enhance RTL-to-GDS methodologies, including floorplanning, synthesis, P&R, STA, signoff, and assembly.Skill
  • Architect and deploy AI/ML-driven solutions in production flows to improve engineering efficiency, turnaround time, and QoR.Skill
  • Optimize EDA tools and custom CAD flows using data-driven and ML-based techniques, in close collaboration with verification, extraction, timing, DFT, and EDA vendors.Skill
  • How to scale AI/ML-driven methodologies across diverse products and advanced technology nodes in real production flows.Skill
  • New ways to blend classical EDA algorithms with modern ML techniques to push PPA and runtime limits.Skill
  • Best practices for deploying, validating, and monitoring ML models in production CAD environments.Skill
  • How to influence next-generation ML-enabled EDA tools and collaborate deeply with cross-functional teams (PV, extraction, timing, DFT).Skill

Parsed by MeritLog from the employer’s own posting. The full description follows below.

Job description

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. Tenstorrent is seeking an Physical Design Engineer to lead cross-functional efforts to solve complex physical design challenges and develop end-to-end RTL-to-GDS methodologies across advanced nodes, with a strong focus on PPA and runtime improvements. The engineer will architect, integrate, and deploy AI/ML-driven solutions into production physical design flows, creating custom CAD tools and partnering with internal teams and EDA vendors to drive next-generation, ML-enabled capabilities. This role is hybrid, based out of Santa Clara, CA or Austin, TX or Fort Collins, CO. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who you are • BS in Electrical or Computer Engineering (or equivalent experience) with 5+ years in Physical Design CAD methodology at advanced nodes. • Proven track record improving PPA and/or runtime on high-performance, low-power taped-out designs. • Hands-on with industry-standard EDA tools (e.g., Fusion Compiler) across synthesis, P&R, STA, signoff, and hierarchical flows. • Strong Python/Tcl and data skills, with interest or experience in ML frameworks (PyTorch, TensorFlow), and the ability to drive complex projects independently. What we need • Lead and contribute to cross-functional efforts solving complex physical design challenges across IPs, projects, and advanced technology nodes. • Develop and enhance RTL-to-GDS methodologies, including floorplanning, synthesis, P&R, STA, signoff, and assembly. • Architect and deploy AI/ML-driven solutions in production flows to improve engineering efficiency, turnaround time, and QoR. • Optimize EDA tools and custom CAD flows using data-driven and ML-based techniques, in close collaboration with verification, extraction, timing, DFT, and EDA vendors. What you will learn • How to scale AI/ML-driven methodologies across diverse products and advanced technology nodes in real production flows. • New ways to blend classical EDA algorithms with modern ML techniques to push PPA and runtime limits. • Best practices for deploying, validating, and monitoring ML models in production CAD environments. • How to influence next-generation ML-enabled EDA tools and collaborate deeply with cross-functional teams (PV, extraction, timing, DFT). Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made. Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer. This position requires access to technology that requires a U.S. export license for persons whose most recent country of citizenship or permanent residence is a U.S. EAR Country Groups D:1, E1, or E2 country. This offer of employment is contingent upon the applicant being eligible to access U.S. export-controlled technology. Due to U.S. export laws, including those codified in the U.S. Export Administration Regulations (EAR), the Company is required to ensure compliance with these laws when transferring technology to nationals of certain countries (such as EAR Country Groups D:1, E1, and E2). These requirements apply to persons located in the U.S. and all countries outside the U.S. As the position offered will have direct and/or indirect access to information, systems, or technologies subject to these laws, the offer may be contingent upon your citizenship/permanent residency status or ability to obtain prior license approval from the U.S. Commerce Department or applicable federal agency. If employment is not possible due to U.S. export laws, any offer of employment will be rescinded.

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