AI Engineer: Edge LLMs & VLMs for Embedded

NXP Semiconductors NV; Netherlands; Sur place; EUR 70 000 - 110 000; Plein temps

Résumé du poste

NXP Semiconductors NV, via TrustMotion, seeks an AI Engineer to join our team working on next-generation AI solutions for embedded platforms. You will focus on development, fine-tuning, optimization, and deployment of LLMs and VLMs, with emphasis on bringing AI from concept to execution on hardware.

The role involves designing, developing, and optimizing AI solutions, fine-tuning models, deploying on embedded/edge platforms, and staying current with AI trends and industry developments.

Qualifications

• BSc or MSc in Computer Science, Electrical Engineering, Software Engineering, AI or related field.
• 2+ years of professional experience.
• Strong programming skills.
• Good understanding of ML and DL fundamentals.
• Hands-on experience with LLMs, VLMs or other Generative AI systems.
• Experience with AI frameworks such as PyTorch, TensorFlow, Hugging Face.
• Understanding of software engineering best practices and version control.

Responsabilités

• Design, develop, and optimize AI solutions based on LLMs and VLMs.
• Fine-tune foundation models for specific use cases and domains.
• Develop and maintain AI agents using modern Agentic Frameworks.
• Design and develop MCP tools and integrate into AI agent workflows.
• Evaluate model performance, accuracy, latency, and resource utilization.
• Deploy and optimize AI models on embedded and edge computing platforms.
• Create proof-of-concepts and support product development activities.
• Stay up to date with emerging AI technologies and industry trends.

Formation

BSc or MSc in Computer Science, Electrical Engineering, Software Engineering, Artificial Intelligence, or a related field

Outils

PyTorch

TensorFlow

Hugging Face

Linux

Description du poste

NXP Semiconductors NV, via TrustMotion, seeks an AI Engineer to join our team working on next-generation AI solutions for embedded platforms. You will focus on development, fine-tuning, optimization, and deployment of LLMs and VLMs, with emphasis on bringing AI from concept to execution on hardware.

The role involves designing, developing, and optimizing AI solutions, fine-tuning models, deploying on embedded/edge platforms, and staying current with AI trends and industry developments.