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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 edgeborn 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 stateoftheart model compression methods and inferencetime optimizations for Small Language Models and Vision Language Models. Together with the team, you will evaluate the performance of optimized models and systems on NXPs embedded systems and will help potential integration of developed methods in NXPs 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 Masters degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Great analytical and problemsolving 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, openminded, 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 .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.