Internship / Thesis Student for Edge AI Optimization for VLMs & VLAs (f/m/d)

Are you inspired by the rapidly evolving world of Edge AI and Efficient Generative Architectures on edge devices, and excited about exploring how these technologies can make a meaningful impact in real‑world applications? Do you want to contribute to cutting-edge research and development that optimizes AI workloads while gaining hands‑on experience in a supportive, high‑tech environment?

Join the Artificial Intelligence Competence Center at NXP and play a key part in shaping the future of intelligent systems.

Key Responsibilities

At the AI Competence Center, we welcome motivated students who are enthusiastic about Edge AI model and system optimization methods and their applications in emerging edge‑born use cases, such as Edge Agentic AI. You will join a collaborative team focused on research, innovation, and engineering in Edge AI.

You will have the opportunity to explore and develop state‑of‑the‑art model compression methods and inference‑time optimizations for Small Language Models and Vision Language Models. Together with the team, you will evaluate the performance of optimized models and systems on NXP’s embedded systems and will help potential integration of developed methods in NXP’s embedded systems.

Your tasks will include, but are not limited to:

• Exploring, designing, and implementing model compression techniques (quantization, sparsity, knowledge distillation, etc.), inference optimizations (e.g., speculative decoding), and efficient generative architecture design.
• Documenting findings with clarity and supporting internal knowledge sharing.
• Working closely with team members to identify promising directions for future development.
• Communicating research outcomes through scientific publications and/or invention disclosures.

Preferred Skills

• Very good understanding of AI/ML concepts (including LLMs, VLMs, Agentic AI) and experience with frameworks such as PyTorch and TensorFlow.
• Familiarity with model compression techniques such as quantization, pruning, and knowledge distillation.
• Understanding of LLM inference optimization techniques including speculative decoding.
• Experience with Python and modern software development practices (modular design, testing).
• Basic knowledge of Linux and Git.
• Experience with edge AI deployment (e.g., TFLite, ONNX, ExecuTorch) is a plus.

Your Profile

• Currently pursuing a Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
• Great analytical and problem‑solving skills, with the ability to work both independently and collaboratively.
• Excellent English communication skills for interacting with a diverse, multinational team across multiple sites.
• Curious, open‑minded, and eager to explore new technologies while contributing to meaningful and impactful AI research.

Duration 

This is a full-time internship (36/40 hours per week) with a duration of minimum six months or longer. Please, note that to be considered for an internship/working student assignment at NXP, you need to be registered as a student during the entire period of the assignment.

More information about NXP in the Netherlands...