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Deploying fully autonomous greenhouses outside every city on earth

Senior Modelling and Control Engineer - Advanced Control Team

£60k – £80k • 0.0% – 1.5%
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Our mission is to grow safer, healthier food by deploying fully autonomous greenhouses outside every city on earth.

High-tech greenhouses are key to our agricultural future - for improving human nutrition and for securing our food system against climate change and population growth. We are doing everything we can to accelerate the deployment of new farms around the world and are well on our way following successful in-field trials of our prototype control system and having reached a partnership agreement to access 25% of the world’s greenhouses.

Find out more about our mission in this 2 min video: youtu.be/LDJ_QdUaap4.


We are an ambitious mission-focussed team with backgrounds from Palantir, DeepMind, Oxford and Cambridge. We are backed by leading deep technology VC funds, including Founders Fund, who backed companies such as SpaceX, Palantir and Square from the start.


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.

As a modelling and control engineer at Optimal you will be directly responsible for the development of control algorithms that will run in the most advanced greenhouses in the world. By joining us at this early stage you will have a significant impact on the journey we take, the problems we tackle, and the team we build.

This role is aimed at an engineer who is looking to step up and play a fundamental role in delivering a product at a fast growing startup. The ideal candidate would have a track record of maturing prototypes into precision engineered products.


-Rapidly develop models of dynamical systems from first principles.
-Write efficient optimisation code to maximise crop yield and quality while minimising energy consumption and carbon emissions.
-Apply modern control theory to push the performance of our control systems; combining control and machine learning approaches where appropriate.
-Write clean, well structured Python/Tensorflow code to help us scale to multiple greenhouses around the world.
-Develop sophisticated monitoring algorithms to detect anomalies in time series sensor data.

Extra credit
- Knowledge of or interest in plant biology.

Meet your team

People you would work with in this role

Richard Mason

Avatar for Richard Mason
Product Manager @ Optimal Labs. PhD in Engineering @University of Oxford . O. Hugo Schuck Prize Winner. YC Fellowship and Entrepreneur First alumni.

Optimal at a glance

Deploying fully autonomous greenhouses outside every city on earth

Optimal focuses on Agriculture. Their company has offices in London. They have a small team that's between 1-10 employees.

You can view their website at http://optimal.ag/ or find them on LinkedIn.

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