Control Systems Engineer
About us
Source.ag is active in leveraging cutting-edge A.I. in greenhouse technology to deliver more fresh produce to the world. The company focuses on creating autonomous greenhouse control products, particularly irrigation systems that optimize water and nutrient delivery to plants, enhancing agricultural efficiency and sustainability.
Job description
As a control systems engineer, you will design real-time irrigation control models using model predictive control, signal processing, and time-series data. You will deploy production systems for autonomous greenhouses, ensuring that these systems operate reliably and efficiently, contributing to a sustainable future in agriculture.
- Architect and operate robust control pipelines that run 24/7, autonomously managing irrigation in greenhouses worldwide
- Design and implement data-driven control logic, such as model predictive control and feedback mechanisms that adapt in real time to plant state, sensor noise, and environmental dynamics
- Own the full system lifecycle — from initial design and experimentation through deployment, monitoring, and continuous improvement in live production
- Bridge control theory and data science to build solutions grounded in physical system dynamics
- Work directly with Plant Scientists and expert growers to translate biological knowledge into control logic and feedback constraints
- Push the boundary where control engineering, signal processing, and applied machine learning converge to deliver state-of-the-art products for growers globally
Relevant work experience
- An MSc or PhD in Control Engineering, Robotics, Mechatronics, Applied Mathematics, Systems Engineering, or a related discipline with a strong control systems component
- At least 4 years of experience in a relevant discipline
- Demonstrated experience building and operating feedback control systems
- Solid signal processing skills: filtering, noise handling, frequency-domain analysis, or sensor fusion
- Familiarity with data-driven control methods such as model predictive control, system identification, or state estimation
- Strong proficiency in Python for production-grade systems
Benefits
Hybrid work environment
Lunch at the office
Flexible hours
Pension contribution of 4.5%
Mental well-being guidance through OpenUp
MacBook Pro 16"
Travel allowance for office commute
Annual learning budget of €1,000
Skills required for the job