Internship / Thesis Student (Edge AI, LLM)

TL;DR

Internship / Thesis Student (Edge AI, LLM): Exploring and developing state-of-the-art model compression and inference-time optimizations for Small Language Models and Vision Language Models on NXP’s embedded systems with an accent on model compression techniques, inference optimizations, and efficient generative architecture design. Focus on evaluating the performance of optimized models and systems and supporting their integration into embedded systems.

Location: Onsite in Eindhoven, Hamburg, or Munich

Company

hirify.global is at the forefront of shaping the future of intelligent systems, focusing on Edge AI and efficient generative architectures on edge devices.

What you will do

• Explore, design, and implement model compression techniques (quantization, sparsity, knowledge distillation) and inference optimizations (e.g., speculative decoding).
• Develop efficient generative architecture designs for Small Language Models and Vision Language Models.
• Evaluate the performance of optimized models and systems on NXP’s embedded systems.
• Help integrate developed methods into NXP’s embedded systems.
• Document findings clearly and support internal knowledge sharing.
• Communicate research outcomes through scientific publications and/or invention disclosures.

Requirements

• Currently pursuing a Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
• Very good understanding of AI/ML concepts (including LLMs, VLMs, Agentic AI) and experience with PyTorch and TensorFlow.
• Familiarity with model compression techniques (quantization, pruning, knowledge distillation) and LLM inference optimization (speculative decoding).
• Experience with Python and modern software development practices (modular design, testing).
• Basic knowledge of Linux and Git.
• Excellent English communication skills for interacting with a diverse, multinational team.
• Must be registered as a student during the entire minimum six-month full-time internship period.

Nice to have

• Experience with edge AI deployment (e.g., TFLite, ONNX, ExecuTorch).

Culture & Benefits

• Join a collaborative team focused on research, innovation, and engineering in Edge AI.
• Opportunity to contribute to cutting-edge research and development.
• Gain hands-on experience in a supportive, high-tech environment.
• Be curious, open-minded, and eager to explore new technologies while contributing to meaningful and impactful AI research.