Prisma-Photonics is a rapidly growing startup company, developing the next-generation smart-infrastructure solution based on novel fiber-sensing technology (smart roads, smart cities, perimeters, and grid monitoring, etc.). The company offers an award-winning disruptive solution; a “sensor free” approach to smart infrastructure. The company is VC backed and in the revenues stage.

Combining pioneering technology in optical fiber sensing with state-of-the-art machine learning, we help prevent environmental disasters, protect human lives, and keep critical energy and transportation backbones running smoothly.

We are seeking a talented, self-driven and passionate Data Science student to join our R&D team and take a meaningful part in overcoming the company’s challenges while maintaining a professional work methodology. The ideal candidate combines strong quantitative skills with solid software engineering practices, and is capable of independently leading end to end data projects, from data preparation to model development and deployment, while also collaborating effectively within a team.

• Interact with complex real-world physical data from different types (spatio-temporal, geo-data, sensors).
• Evaluate model accuracy, diagnose and analyse errors, and communicate results with clear metrics and visualizations.
• Train, optimize and deploy AI models for predicting physical quantities (e.g. wind speed) from spatiotemporal sensor data.
• Develop Tools for data processing, analysis, and visualization.
• Production‑Grade Engineering – Write, test, and maintain reliable code that operates 24/7 in production and integrates seamlessly with utility systems.
• Work in a dynamic environment of short life cycle research and development.
• Support and troubleshoot live ML pipelines – monitor production models, investigate anomalies, retrain and redeploy when needed, and keep accuracy high.
• Collaborate with customer-facing teams to tailor models and features to customer-specific data, quickly resolving field issues and delivering real-world value.

• Studying for Msc/PhD or last Year Bsc degree in a relevant field (Computer Science, EE, Physics, etc).
• Motivated, eager to tackle challenges with a “can do attitude”.
• Excellent communication and teamwork skills. Strong Data analysis and Presentation skills.
• Strong Python programming skills, with the ability to write clean, modular, and testable production-grade code.
• Experience with ML and numerical libraries (NumPy, Pandas, Scikit-learn, Pytorch, etc.).

• Experience applying machine learning to real-world signal problems, such as computer vision (CV), audio analytics, or structural health monitoring.
• Familiarity with MLOps tools and best practices, such as experiment tracking and reproducibility using platforms like TensorBoard, Weights & Biases, or ClearML.