> Markdown version of [/jobs/ext/1791093-cad-flow-engineer-physical-implementation-sign-off-ai-hardware](https://www.wearedevelopers.com/jobs/ext/1791093-cad-flow-engineer-physical-implementation-sign-off-ai-hardware). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # CAD Flow Engineer, Physical Implementation & Sign Off, AI Hardware - **Company:** Tesla Motors - **Location:** Palo Alto, CA, United States - **Salary:** $128,000.0 - $312,000.0 - **Contract:** Permanent contract - **Skills:** Computer-Aided Design, Artificial Intelligence, Very-Large-Scale Integration, Artificial Neural Networks, Computer Engineering, Electronic Design Automation, Machine Learning, Linux Virtual Server, Power Analysis (Cryptography), Physical Verification, Hardware Acceleration, Physical Design, Cts+ - **Published:** July 3, 2026 - **Apply:** https://jobs.localjobnetwork.com/apply/add/86899121/1 ## About the Role * Degree in Electrical Engineering, Computer Engineering, or related field, or equivalent work experience * 5+ years of CAD flow development and physical implementation experience on complex SoCs * Deepexpertisein CTS methodologies and clock architecture optimization for PPA * Hands-on experience with industry P&R and synthesis tools (Innovus, Genus, Fusion Compiler, or equivalent) * Strong command of ECO methodologies - timing, functional, and metal ECO flows throughtapeout * Experience building power analysis and power intent flows (UPF/CPF, multi-voltage) * Proficiencywith signoff integration - STA, EMIR, DRC/LVS, and parasitic extraction within a unified flow * Ability to develop, deploy, and scale agentic AI flows for design automation and autonomous closure ## Description The Tesla AI Hardware team is at the forefront of revolutionizing artificial intelligence throughcutting-edgehardware innovation. Comprising brilliant engineers and visionaries, the team designs and develops advanced AI inference chips tailored to accelerate Tesla's machine learning capabilities. A key part of this effort is Dojo, Tesla's custom supercomputer system built to efficiently train massive neural networks on vast video data from the fleet. The work of Tesla's AI Hardware team powers the neural networks behind Full Self-Driving (FSD), and Tesla humanoid robot, Optimus, pushing the boundaries of computational efficiency and performance. By creating custom silicon and optimized architectures, the team ensures Teslaremainsa leader in AI-driven automotive and energy solutions, shaping a future where intelligent machines enhance human life. Tesla's AI Hardware Team is looking for experienced, highly skilled VLSI engineers who enjoy working across the logic, circuit,methodology, and physical design levels. Our physical design team is growing to tackle a wider range of projects,building onour in-house SOC designexpertise. This position entails the design,constructionand integration of SOCs, IP, circuits, tool flows, and methodologies into systems using advanced technologies - from definition through characterization. Our AI Hardware engineering team builds andmaintainsthe end-to-end CAD infrastructure that powerstapeoutfor complex SoC and 3D IC designs. As a Staff CAD Flow Engineer, you will own the development, deployment, and continuous improvement of implementation and signoff flows - from RTL to GDS. You will be at the center of how we scale design productivity and PPA optimization using agentic AI-driven flows. What You'll Do * Build andmaintainRTL-to-GDS implementation flows including synthesis, placement, routing, and signoff integration * Own CTS flow development and optimization - tune clock tree strategies to achieve PPA targets across frequency, power, and area * Develop and manage ECO flows - functional ECOs, timing ECOs, and metal-only ECOs - with robust LEC validation at each stage * Set up andvalidateelectrical analysis flows including static/dynamic IR drop, EM, and power analysis integration within the implementation flow * Develop power intent flows - implement and validate UPF/CPF-driven multi-voltage domain strategies through synthesis and P&R * Maintainparasitic extraction flows and ensure correlation between implementation and signoff tools * Build MMMC timing flows - manage corner and mode configuration for setup, hold, and signoff convergence * Integrate physical verification (DRC/LVS) and formal equivalence checking (LEC) as continuous checkpoints within the flow * Develop and deploy agentic AI flows to automate flow execution, detect bottlenecks, triage violations, and drive closure decisions without manual intervention * Evaluate and adopt new EDA tool capabilities - drive tool bring-up, qualification, and regression benchmarking ## Related Videos - [Developing an AI.SDK](https://www.wearedevelopers.com/videos/198-developing-an-ai-sdk) - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [Building a fully automated escape room](https://www.wearedevelopers.com/videos/735-building-a-fully-automated-escape-room) - [What non-automotive Machine Learning projects can learn from automotive Machine Learning projects](https://www.wearedevelopers.com/videos/397-what-non-automotive-machine-learning-projects-can-learn-from-automotive-machine-learning-projects) - [How Machine Learning is turning the Automotive Industry upside down](https://www.wearedevelopers.com/videos/61-how-machine-learning-is-turning-the-automotive-industry-upside-down) - [Code to Road in < 12 hours](https://www.wearedevelopers.com/videos/1082-code-to-road-in-12-hours) ## Related Articles - [How software is steering vehicle technology](https://www.wearedevelopers.com/magazine/515-how-software-is-steering-vehicle-technology) - [Best US AI Conferences for CTOs in 2026: Build vs. Buy, Vendor Evaluation, and Peer Intelligence](https://www.wearedevelopers.com/magazine/736-best-us-ai-conferences-for-ctos-in-2026-build-vs-buy-vendor-evaluation-and-peer-intelligence) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Never delegate the understanding](https://www.wearedevelopers.com/magazine/749-never-delegate-the-understanding) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers)