About Spur Insights
Spur Insights, located in Zurich, Switzerland, specializes in developing cutting-edge Data Science, machine learning, and AI solutions aimed at enhancing the efficiency and reliability of industrial processes and machines. Our innovative solutions are utilized globally by clients in over 100 countries, spanning various sectors including manufacturing processes in the plastics, electronics, and converting industries.
Your Role
As a member of our team, you will focus on designing, building, and deploying Large Language Model (LLM)–based solutions that integrate machine data, operator knowledge, and industrial processes.
Your Responsibilities
- Develop Agentic-LLM solutions to capture, structure, and reason over machine documentation, operator input, and historical service data.
- Build AI-driven self-diagnostic and advisory systems to detect wear and tear, impending mechanical issues, and incorrect machine settings.
- Design natural language interfaces and reasoning layers to assist machine operators in troubleshooting, quality control, and energy efficiency decisions.
- Fine-tune, evaluate, and integrate LLMs for industrial use cases, with a strong emphasis on accuracy, robustness, and explainability.
- Collaborate closely with clients to understand machine behavior, data availability, and operational constraints, translating these insights into scalable AI solutions.
You will engage hands-on throughout the entire lifecycle, from data exploration and model development to deployment and iteration in real industrial environments.
What We Are Looking For
- Strong foundations in Data Science with a clear focus on generative AI and LLM-based systems.
- Proficiency in Data Science-centric languages and environments such as Python, Jupyter, TensorFlow, or Matlab.
- Knowledge of generative AI and LLM.
- Effective communication skills and the ability to thrive in a collaborative team environment.
- Interest in or exposure to industrial data, machine engineering, or complex physical systems.
How to Apply
Apply online using the form below. Please note that only applications matching the job profile will be considered.