AI Simulation and Control Engineer at well-funded AI infrastructure startup

You will develop and deploy advanced AI agents to manage critical physical infrastructure, starting with high-tech greenhouses. By adapting state-of-the-art simulation models and training them on proprietary data, you will take real-time control of complex actuators. This role bridges the gap between machine learning and physical world optimization to drive global productivity.

Well-funded AI infrastructure startup

• Adapt and train state-of-the-art simulation models using proprietary data from advanced physical environments.
• Integrate machine learning models into real-time control frameworks to manage complex hardware actuators.
• Monitor and optimize AI performance to maximize industrial yields while minimizing resource consumption.

• Strong background in machine learning, numerical simulation, and control systems like Model Predictive Control.
• Proficiency in software engineering using Python, with experience in Julia being a significant bonus.
• Hands-on experience with modern AI coding tools, version control, and containerized deployment processes.

• Work on world-first AI control systems for critical infrastructure with immediate, real-world environmental and economic impact.
• Backed by top-tier VCs and world-renowned AI research leaders from major global labs.
• High-impact, early-stage opportunity offering significant equity and the chance to shape the future of autonomous industry.