Founding AI Simulation and Control Engineer

Optimal’s Mission

Optimal is building AI agents to control the world’s most critical infrastructure - from factories, to datacenters, and starting with high-tech greenhouses.

We are backed by the Director of AI Research at Google Deep Mind, a Board Member at Meta, as well as early VCs in Space

X, Anduril, and Palantir.

We have already built the world’s most advanced AI control for high-tech greenhouses and have proven breakthrough performance in customer greenhouses. We are actively scaling to more greenhouses and have signed integration partnerships allowing us to access 75% of the world’s greenhouses.

High-tech greenhouses are key to our agricultural future - for improving human nutrition and securing our food system against climate change and geopolitical instability. But the shortage of skilled operators causes existing greenhouses to underperform and prevents new greenhouses being built.

Our AI increases the profits of individual greenhouses by >$1M/year, increases yields, reduces energy and water usage, and unlocks global greenhouse expansion. There are 8,000 high-tech greenhouses in the world today giving Optimal an opportunity to create >8B/year of productivity gains. And by overcoming the shortage of skilled operators, we enable the rapid deployment of new greenhouses outside cities across the world.

As a Founding AI Simulation and Control Engineer, you will have direct responsibility for the development and deployment of Optimal's AI agents at the most advanced greenhouses in the world.

You will play a critical role in delivering AI to these greenhouses.

This role is aimed at an ambitious engineer who is looking to play a fundamental role in delivering AI product at a fast growing startup.

• Visit a high-tech greenhouse to understand crops, hardware, and the underlying physical/biological processes.
• Adapt Optimal’s state-of-the-art simulation models to the greenhouse of a new customer and train the models on proprietary data from that greenhouse.
• Integrate the simulation models into Optimal’s AI control framework, taking real time control of all of the greenhouse actuators.
• Deploy LLM agents to interact with customers and autonomously manage Optimal's AI control.
• Monitor, review and continuously improve the performance of Optimal's AI to maximise crop yields and minimise resource consumption, working closely with our agronomy experts.

• Strong background in at least one of Machine Learning, Optimisation, Control (Model Predictive Control, Optimal Control, and classical feedback techniques), Reinforcement Learning, Physics Modelling and Numerical Simulation.
• Experience training Machine Learning models.
• Experience creating and deploying LLM agents and workflows.
• AI-native coding.
• Software engineering in Python (Julia is a bonus)
• Software engineering processes and tools (containers, version control, deployments etc)