Optimal

Senior Control Engineer at Optimal

Rotterdam · Full Time

We are a collection of engineers and scientists from Oxford, MIT and DeepMind, on a mission to grow safer, healthier food by deploying fully autonomous indoor farms outside every city on earth. Backed by world-leading deep technology funds, including Founders Fund.

Apply to Optimal

Job Description

THE MISSION AND TEAM

We are a collection of engineers and scientists from Oxford, MIT and DeepMind, on a mission to grow safer, healthier food by deploying fully autonomous indoor farms outside every city on earth.

Our team includes a professor of control engineering, a research scientist who helped reduce the cooling bill of a Google data centre by 40%, and a farmer who started as a vegetable picker 40 years ago and now runs one of the most advanced indoor farming operations in the world.

We are backed by world-leading deep technology VC funds, including Founders Fund, who have backed companies such as SpaceX, Palantir and Square from the very start. We are well capitalised for the future having raised one of the largest seed rounds ever in Europe.

YOUR ROLE

Our belief is that the next step-change in productivity for agriculture will come from the automatic control of large-scale greenhouses. We think that modern control methods can have a major impact on productivity, whilst minimising the energy inputs required to grow crops. Achieving this goal is crucial for supporting a larger population: the world’s population is expected to reach 10bn by 2050 and agriculture already accounts for 70% of global freshwater withdrawals.

As a senior control engineer you will play a key role in designing and implementing control systems in our $50m greenhouses. You will also work closely with our research team, and contribute to combining control theory with machine learning in a principled way.

YOUR RESPONSIBILITIES

- Install, test and deploy control systems, utilising modern control techniques.
- Model dynamical systems using first-principles and data-driven approaches, exploiting our deep, proprietary dataset.
- Prepare and approve specifications, test protocols and other documents to define functionality.
- Work with our professor-level research supervisors to analyse results and iterate approaches.
- Work closely with our machine learning research teams to advise on modelling and optimisation.
- Continually learn and self-improve, helping others to do the same.

YOUR SKILLS AND EXPERIENCE

- Advanced degree (or equivalent experience) in control theory.
- 2+ years of industrial experience as an engineer.
- Experience modelling and simulating dynamical systems using first-principles and data-driven approaches.
- Applied control and optimisation experience: controller design, implementation, deployment and evaluation.
- In depth knowledge of some area of modern control e.g., Robust, MPC, Stochastic, Networked Control
- Good programming skills in a general purpose programming language e.g., Python/C++.
- Knowledge of control systems/instrumentation standards used in industry such as PLC, SCADA, DCS.

Extra credit
- Experience with managing the deployment of a control system, especially building controls/HVAC.
- Software development experience in a commercial environment.
- Strong publication record in relevant journals/conferences.
- Knowledge or willingness to learn machine learning approaches for time series modelling: GPs, RNNs, Bayesian NNs, etc., as well as techniques from reinforcement learning to complement your skills.

Apply Now

What We're Building

We are a collection of engineers and scientists from Oxford, MIT and DeepMind, on a mission to grow safer, healthier food by deploying fully autonomous indoor farms outside every city on earth.

Our team includes a professor of control engineering, a research scientist who helped reduce the cooling bill of a Google data centre by 40%, and a farmer who started as a vegetable picker 40 years ago and now runs one of the most advanced indoor farming operations in the world.

We are backed by world-leading deep technology VC funds, including Founders Fund, who have backed companies such as SpaceX, Palantir and Square from the very start. We are well capitalised for the future having raised one of the largest seed rounds ever in Europe.

Other Jobs at Optimal

Optimal Team

David Hunter
Founder/CEO @Optimal. Deep Reinforcement Learning research @University of Oxford. Algorithmic trading @Deutsche Bank.
João Abrantes
CTO @Optimal. Machine Learning and Robotics research at @EPFL .
Richard Mason
Senior Engineer @ Optimal Labs. PhD in Engineering @University of Oxford . O. Hugo Schuck Prize Winner. YC Fellowship and Entrepreneur First alumni.
QIXUAN FENG
Engineer @ Optimal Labs, MSc in Computer Science from Oxford.

Optimal Investors

Philipp Moehring
Managing everything Europe (funds, syndicates) @AngelList. Investing in early stage tech companies in Europe. Connecting founders, investors & talent.
Nathan Benaich
Investing in intelligent systems.
Michael Orland
Currently: trying my hand at angel investing. Previously: CRO @Songkick, MBA @London Business School, PM @Rave Wireless, PM @Vindigo
See More