At Source.ag, we're on a mission to power a sustainable future by leveraging cutting-edge A.I. in greenhouse technology to deliver more fresh produce to the world. Our values drive everything we do to support this mission; they shape how we work, collaborate, and achieve our goals:
🧑🌾 All In for our Growers: We work closely with growers, prioritizing their needs.
🌈 Strength through Diversity: We embrace different perspectives and backgrounds, fostering a culture of mutual respect, inclusion, and collaboration.
🌟 Learn–Adapt–Succeed: We grow through continuous feedback, learning, and dedication.
🚀 Driven to Deliver: We are dedicated to delivering impactful results.
🌱 Plant Solutions: We plant solutions that shape the future of food production.
Our autonomous greenhouse control product is at the heart of this mission, specifically our irrigation autopilot. Imagine an intelligent system that precisely delivers the optimal amount of water and nutrients to plants exactly when they need it, every single day. This isn't just about efficiency; it's about driving stronger plants, higher yields, and a more resilient global food supply.
This system is far from simple. Think of it as the adaptive cruise control of a modern car — but instead of steering vehicles, you're steering plants. It's a complex, dynamic environment with numerous constraints, conflicting objectives, noisy sensor data, and significant time lags, and it runs live 24 hours a day, 7 days a week.
We're looking for a Control Systems Engineer with a strong control systems background who thrives on building production systems where failure is not an option. You combine the rigour of a control engineer — feedback loops, signal processing, state estimation — with the pragmatism of a data-driven practitioner who can design, deploy, and own systems in live operation.
In our Control team, you'll be embedded in a highly collaborative environment, working side by side with Data Scientists, Software Engineers, Product Managers, and AI Solution Specialists. Together, you'll explore, design, ship, and continuously support new models and products in live operations. What makes this role truly unique is the direct collaboration with Plant Scientists and expert growers, allowing you to integrate cutting-edge biological knowledge and real-world practices directly into your work.
What we would like you to get excited about:
Architect and operate robust control pipelines that run 24/7, autonomously managing irrigation in greenhouses worldwide — systems that must be reliable, observable, and safe to fail gracefully
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
You have:
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 — you have designed, deployed, or maintained a live control loop
Solid signal processing skills: filtering, noise handling, frequency-domain analysis, or sensor fusion; you know what to do when your data is messy and your sensors lie
Familiarity with data-driven control methods such as model predictive control, system identification, or state estimation (Kalman filtering or equivalent)
A systems mindset: you think about what happens when things go wrong — sensor failures, edge cases, degraded modes — and design for resilience as well as performance
Strong proficiency in Python for production-grade systems
Experience with data-driven modelling for physical systems: regression, time series, or physics-informed approaches applied to real process data
Proficiency with AI tools, since we use them to scale our output; our philosophy is: "AI is your collaborator, but you are accountable for the result"
Clear, concise communication skills, with the ability to explain control system behaviour to non-technical stakeholders, including growers and product teams
Nice to have:
Experience with ML model development and deployment
Background in process control, agricultural systems, or biological/physical modelling
Familiarity with time-series databases, IoT sensor pipelines, or embedded system constraints
Our offer in return for your talent and skills:
A hybrid work environment: we have office days on Mondays and Thursdays, and we make them worthwhile
Lunch at the office
Flexible hours, always respecting your team and meetings
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
One-off work-from-home budget of €550
Monthly Wi-Fi and phone plan reimbursement of €50
Unlimited holidays, with an expectation that you take at least 25 per year
🌱 Ready to grow with us?
At Source, we highly value diversity of backgrounds and perspectives. Research shows that people assess their fit for roles differently, so we strongly encourage you to apply even if you feel you don’t tick all the boxes.
Note to recruitment agencies: We do not appreciate unsolicited outreach or external acquisition regarding our open roles. Please refrain from contacting us about these vacancies. Thank you.
