Key Skills

Job Description

Now Hiring: Data Scientist in high-tech scale-up Location: Delft, on-site At Luo, we build machines that automate quality inspections of medicine. In many pharmaceutical environments, people still spend hours manually checking products for particles, cosmetic defects, and packaging integrity issues. It’s tedious, and humans make mistakes. Our machines do this job more accurately, faster, and more consistently. The brains of our machines are the detection models: algorithms that decide in real time whether a product passes inspection. We’ve proven the technology works. Now we’re scaling, which means more clients, more applications, and higher accuracy. For that, we need someone who builds, improves, and pushes these models to the next level. Our office is located at YES!Delft, surrounded by dozens of other tech start-ups and scale-ups, right next to TU Delft. Much of the work happens hands-on, with our machines, test setups, and the teams around them. The Role We are looking for a Data Scientist who enjoys developing and optimizing machine learning models for real-world applications. Not just running models and reporting results, but understanding what has impact and executing what must be done to make it better. Most of the time, that is more than just re-training. You’ll work on detection models for particle contamination, cosmetic defects, and closure integrity problems. You stay on top of the latest developments in the field, translate them into concrete improvements, and ensure our models meet the strict requirements of the pharmaceutical industry. You work closely with the Software, Quality Support, and Machine Vision teams, who support you as you grow in the role. What you’ll work on Staying up to date: Following the latest developments in detection models and AI, assessing what’s relevant for our custom models, and translating this into concrete research actions. Building and improving detection models: Adapting existing models to new clients, improving detection, and qualifying model performance offline. Orchestrating data strategy: Managing and executing dataset annotation for model training and defining which data needs to be available to build and improve the best detection models. What we are looking for Education: A bachelor’s (HBO) or master’s degree in data science, AI, Computer Science, or a related field. Strong ML foundation: You have hands-on experience with Python and machine learning frameworks such as PyTorch or TensorFlow, gained at work or during your studies, graduation project, or internship. Data analysis: You have a strong focus on analyzing image data, understanding patterns, and extracting meaningful insights to improve model performance. Experience with medical or industrial datasets is a plus. Hands-on experience: You are comfortable owning the full pipeline, including data collection, annotation, and running experiments independently, or you’re eager to learn this quickly. Analytical and communicative: You can explain complex findings clearly to non-technical people and know how to tailor your message to your audience. Languages: You are highly proficient in Dutch and English, both spoken and written. Both languages are used daily, within our team and with our clients. Eye for quality: You recognize that accuracy is critical in the pharmaceutical industry and understand the real-world impact of your models, especially when it comes to patient safety. Direct and transparent: You communicate openly about challenges. If a model underperforms or data is insufficient, you raise your concerns early so we can solve them together. Office-based work is required, allowing for fast communication and close collaboration with your team. Dutch/EER working permit What it’s like to work here Real impact: Your models run in real machines at real client sites. When you improve something, you directly see the effect! Flat structure, short lines: Good idea? Go for it. Our structure is simple to encourage involvement, creativity, and innovation. Interesting challenges: Detection problems in the pharmaceutical industry are complex and demanding. You’ll work at the edge of technology, where quality standards are high. A solid team: You work alongside engineering, operational, and commercial teams who all share the same goal. Cooperation and teamwork are key to building and delivering machines that actually work. Ready to build detection models that make a difference? Send your CV and a short intro to [email protected]

Core Responsibilities

Develop, adapt, and improve machine-learning detection models for pharmaceutical product inspection, including particle contamination, cosmetic defects, and closure integrity. Guide data strategy by managing dataset annotation, identifying data needs, evaluating model performance, and applying relevant advances in AI and detection methods.

Requirements

A bachelor’s or master’s degree in data science, AI, computer science, or a related field is required, along with hands-on Python and machine-learning framework experience. Candidates should be strong in image-data analysis, able to manage or learn the full data and experimentation pipeline, communicate clearly, and be proficient in Dutch and English; medical or industrial dataset experience is a plus.