Thesis Student for Edge AI Optimization Research & Engineering

Experience: Not Available to Not Available years

Location: Eindhoven, Netherlands

Skills: AI, Machine Learning, Edge AI, model compression, quantization, sparsity, knowledge distillation, inference optimizations, speculative decoding, Python, PyTorch, TensorFlow, Linux, Git, TFLite, ONNX, ExecuTorch

Your Team
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 responsibilities
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.

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.

Preferred Skills
Very valuable 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.

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. We encourage applicants to upload their grade transcripts as part of their application. While optional, it helps us gain a clearer understanding of your academic background when reviewing your profile. More information about NXP in the Netherlands... #LI-f5d0

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