AI/ML driven ASIC Design and Implementation Automation Engineer

Location: San Diego (Treena St)

Time Type: Full time

Job Description

As an “AI/ML driven ASIC Design and Implementation Automation Engineer” in our Advanced Chip Engineering (ACE) organization, you will work in a dynamic environment to explore methodology, flows and tools to improve efficiency and quality of results (power, performance, area, and quality) for SoC and IP development teams across the organization. You'll be working and connecting with AI/ML and automation experts in the industry as well as academia to explore state-of-the-art AI/ML CAD techniques as a part of VLSI CAD SW, prescribe key methods and requirements for tools & features to leverage for ASIC design.

In this role, you will develop prototype solutions to evaluate various state-of-the-art AI/ML techniques to identify the best solutions for NXP designs. While exploring these new ways of working, successful candidates will be working on actual designs and implementation to pilot and develop the automation.

This opportunity is within ACE 'Design Methodologies and Automation' organization to enable Digital Transformation to leverage state-of-the-art AI/ML ideas to improve NXP designs for the Automotive Processors and Advanced microcontrollers in NXP.
The right candidate will be working in a fast-paced engineering environment, on a leading-edge advanced node technologies enabling automated building of exciting and complex SoCs.
 

Job Summary:

• Explore research ideas and solutions that bring AI/ML applications to VLSI design

• Work closely with Academic research communities in AI/ML for VLSI design, Architecture teams, IP and SoC designers and SoC Implementation teams from multiple sites to explore and evaluate for leading edge SoC technologies serving multiple industries

• These automation applications include use of GenAI, Reinforcement Learning, Graph Neural Networks, and convolutional Networks

• Strong AI/ML expertise and software background required
   

Qualifications:

• BS or MS in Computer Science, Electrical Engineering, Computer Engineering or related disciplines with strong background in SW development

• Hands-on expertise in programming using Python/C++

• <1 year of experience in AI and ML techniques (LLMs, CNN, RNN, and GraphNN) with experience of application to real world optimization problems

• Data structures, algorithms, and SW development for optimization problems

• Hands on experience in Unix/Linux, revision control (Git, BitBucket), SW development and debug tools

• Excellent analytical problem-solving skills

• Strong verbal and written communication skills

Desirable skills/experience:

• Understanding or prior experience with EDA tools for design, verification, DFT and implementation

• Experience with Design revision control (GIT, DesignSync) and Make

• Splunk, Jenkins, LSF and CI/CD process

Job location:

• San Diego, CA

The base salary range for this position is as mentioned below per year. We also provide competitive benefits, incentive compensation, and/or equity for certain roles.
Company benefits include health. dental, and vision insurance. 401(k), and paid leave. Please note that the base salary range (OR hourly rate) is a guideline, and individual total compensation may vary based on a number of factors such as qualifications, skill level, work location, and other business and organizational needs. This base pay range is specific to California and is not applicable to other locations. A reasonable estimate of the base salary range as of the date of this posting is:

$117,800 to $162,000 annually

More information about NXP in the United States...

NXP is an Equal Opportunity/Affirmative Action Employer regardless of age, color, national origin, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, marital status, status as a disabled veteran and/or veteran of the Vietnam Era or any other characteristic protected by federal, state or local law. In addition, NXP will provide reasonable accommodations for otherwise qualified disabled individuals.

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