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NXP Semiconductors · Multiple locations

# AI Engineer – Foundational Models with Multi-Modality (Analog IC Design)

Multiple locations Design 

Listed on NXP Semiconductors’s official careers site. Posted October 9, 2026. Check that it is still open and apply there.
[Apply on NXP Semiconductors’s careers site →](https://nxp.wd3.myworkdayjobs.com/careers/job/Eindhoven/AI-Engineer---Foundational-Models-with-Multi-Modality--Analog-IC-Design-_R-10066844)

[OpenNash Jobs](https://jobs.opennash.com/) / [NXP Semiconductors](https://jobs.opennash.com/companies/nxp-semiconductors/) / AI Engineer – Foundational Models with Multi-Modality (Analog IC Design)

## Job description

Being part of the NXP Design Enablement (DE) global team as a CAD Methodology & Flow Engineer offers a unique opportunity to work at the intersection of semiconductor design, software engineering, and AI innovation.

In this role, you will: Help establish, together with the NXP IP team, efficient, best-in-class methodologies and tools that support NXP design centers worldwide. Play a key role in shaping the future of analog IC design through the integration of Generative AI technologies. Collaborate with international teams to enhance our internal chatbot platform (built with Streamlit and AWS Bedrock), making it more context-aware and capable of understanding analog IC terminology, abbreviations, and synonyms.

Work in a multicultural, global environment alongside NXP design organizations across the world. Join a worldwide team of experts recognized as technical leaders in this unique and highly competitive domain. Do you want to work in an exciting company that is at the heart of innovation? Join us and learn something new every day! Your Profile

### Education & Experience

At minimum MS/MSc degree in electrical engineering with software expertise with a minimum 5 years’ experience. Relevant hands-on experience with GNNs, and open-source multi-modal foundational models. Preferably analog IC design knowledge or affinity with analog design. Programming Languages Python software expert - Python object-oriented programming Experience with Pytorch/Tensorflow/Huggingface, and/or CUDA Linux environment and Compilation (Bash / CMake) Amazon Web Services (AWS) Bedrock, Lambda Database knowledge AI & Knowledge Management Build and maintain a domain-specific knowledge base to support semantic understanding of analog IC concepts.

Collaborate with cross-functional teams to ensure seamless integration of AI tools into existing design environments. Experience with MLOps practices and deployment pipelines. Familiarity with vector databases and semantic search technologies.

### Professional Skills

Highly developed verbal and written communication skills in English. Strict towards performance and quality requirements. Demonstrates good analysis and problem-solving skills. Must have effective interpersonal, teamwork, and communication skills. Must have the ability to multi-task in a fast-paced environment. Collaborative skills for working efficiently in a team having worldwide connections with partners and users. Self-driven and passionate about learning and the IC industry.

Strong documentation and technical writing skills. Proactive mindset with a focus on continuous improvement and innovation. Experience with the following items is a plus Open-source frameworks such as Docker, concepts such as containerization Configuration management tools (e.g. Git) Experience with CI/CD frameworks Ticketing system/Bug-tracking tools (e.g. Jira) Testing platform knowledge e.g. Robot Framework OSS basic knowledge (which OSS can be reused or not, copyright management) Object-Oriented Programming (C/C++, Python, …) Cadence SKILL Streamlit More information about NXP in the Netherlands... #LI-f5d0

## At a glance
- Posted by the employer: Oct 9, 2026
- First seen by OpenNash: Oct 12, 2026
- Last checked: Oct 19, 2026
- Listed for: 10 days
- Location: Multiple locations[Apply on NXP Semiconductors’s careers site →](https://nxp.wd3.myworkdayjobs.com/careers/job/Eindhoven/AI-Engineer---Foundational-Models-with-Multi-Modality--Analog-IC-Design-_R-10066844)

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