Principal Engineer, Automated Derivatives

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profile Job Location:

Austin, TX - USA

profile Monthly Salary: Not Disclosed
Posted on: 15 hours ago
Vacancies: 1 Vacancy

Job Summary

In this multi-disciplinary role you will lead the end-to-end delivery of derivative SoCs focusing on the intersection of RTL design functional verification and physical implementation. You will not just execute flows; you will build an AI-augmented Silicon Factory that uses machine learning to bridge the gap between architectural intent and GDSII. Your goal is to achieve ultra-fast turnaround times by using AI to predict physical outcomes during RTL coding and to automate the verification of design variants.

Key Responsibilities

1. AI-Augmented RTL & Architecture

  • Physical-Aware RTL: Use ML-based predictors to evaluate RTL code for timing and congestion bottlenecks before synthesis reducing the number of RTL-to-GDS iterations.
  • Derivative Generation: Develop scripts and Generative AI prompts to automate the creation of RTL wrappers memory maps and bus interconnects for design variants.
  • Logic Optimization: Employ AI to identify redundant logic or clock-gating opportunities to hit aggressive power targets in derivative designs.

2. Intelligent Verification

  • Automated Testbench Scaling: Build AI-driven verification environments that automatically adjust constraints and coverage goals when a design derivative (e.g. changed cache size or port count) is instantiated.
  • Smart Regression Management: Use ML to prioritize test cases that are most likely to fail based on historical RTL changes slashing simulation time and compute costs.
  • Bug Prediction: Deploy pattern-recognition models to identify bug-prone modules in the RTL based on complexity metrics and previous tape-out data.

3. Rapid Physical Implementation

  • Seamless Handoff: Ensure a zero-friction path from RTL to Physical Design by using AI to automatically generate floorplan constraints and timing assertions from the design spec.
  • Closure Acceleration: Drive the physical implementation of derivatives using AI to reuse placement and routing solutions from parent designs to achieve 10x faster convergence.

Qualifications :

  • Education: Minimum of a Masters degree in Electrical Engineering Computer Science or Computer Engineering.
  • Experience: 1215 years of professional experience in the semiconductor industry with a focus on:
    • Full-Stack Hardware Mastery: Proficiency in SystemVerilog for RTL design and UVM for functional verification.
    • Physical Design Foundation: Solid understanding of Synthesis P&R and STA (Static Timing Analysis) to ensure RTL is physically realisable.
    • ML/AI Integration: Expert Python skills to build and deploy models that interface with both simulation tools (VCS Xcelium) and implementation tools (Innovus ICC2).
    • Data-Driven Flow Dev: Experience using Tcl/Python to extract features from simulation logs and implementation reports to train predictive models.
    • Version Control & CI/CD: Mastery of Git and CI/CD pipelines (Jenkins/GitLab) to manage the high-velocity deployment of design derivatives.

Additional Information :

Renesas is an embedded semiconductor solution provider driven by its Purpose To Make Our Lives Easier. As the industrys leading expert in embedded processing with unmatched quality and system-level know-how we have evolved to provide scalable and comprehensive semiconductor solutions for automotive industrial infrastructure and IoT industries based on the broadest product portfolio including High Performance Computing Embedded Processing Analog & Connectivity and Power.
 
With a diverse team of over 22000 professionals in more than 30 countries we continue to expand our boundaries to offer enhanced user experiences through digitalization and usher into a new era of innovation. We design and develop sustainable power-efficient solutions today that help people and communities thrive tomorrow To Make Our Lives Easier.     
 
At Renesas you can: 

  • Launch and advance your career in technical and business roles across four Product Groups and various corporate functions. You will have the opportunities to explore our hardware and software capabilities and try new things.  
  • Make a real impact by developing innovative products and solutions to meet our global customers evolving needs and help make peoples lives easier safe and secure. 
  • Maximize your performance and wellbeing in our flexible and inclusive work environment. Our people-first culture and global support system including the remote work option and Employee Resource Groups will help you excel from the first day.    

Are you ready to own your success and make your mark  

Join Renesas. Shape Your Future with Us.  

Renesas Electronics is an equal opportunity and affirmative action employer committed to celebrating diversity and fostering a work environment free of discrimination on the basis of sex race religion national origin gender gender identity gender expression age sexual orientation military status veteran status or any other basis protected by federal state or local law. For more information please read our Diversity & Inclusion Statement.

Renesas Electronics deals with dual-use technology that is subject to U.S. export controls regulations. Under these regulations it may be necessary for Renesas to obtain U.S. government export license prior to release of technology to certain persons. The decision whether or not to file or pursue an export license application is at the sole discretion of Renesas.

We have adopted a hybrid model that gives employees the ability to work remotely two days a week while ensuring that we come together as a team in the office the rest of the time. The designated in-office days are Tuesday through Thursday for innovation collaboration and continuous learning.


Remote Work :

No


Employment Type :

Full-time

In this multi-disciplinary role you will lead the end-to-end delivery of derivative SoCs focusing on the intersection of RTL design functional verification and physical implementation. You will not just execute flows; you will build an AI-augmented Silicon Factory that uses machine learning to bridg...
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