At Gigaton, we're on a mission to reduce industrial carbon emissions on a gigaton scale, by putting the latest advances in machine learning to work in some of the planet's most energy-intensive industries (like cement, steel and glass). Our systems directly control industrial plants in real time, running them more efficiently and stably, cutting costs and carbon year on year - building the foundations for the next industrial revolution.
We're proud nerds, thinkers and doers, all devoted to engineering the tools required to deliver fully autonomous plant control to energy-intensive industries, while removing gigatons of carbon from our atmosphere. And having a gigaton of fun as we go.
We have exceptionally high standards for what we build and who we build it with, always pushing and celebrating each other in equal measure. We care about deep tech, but we care even more about whether it delivers cost and carbon impact in a live plant, with real people, under real constraints.
With Gigaton, you'll solve really tough problems in places few people ever get close to, and build something that actually helps the planet. Building autonomous plants that decarbonise energy-intensive industries is a monumental ask. Are you up for it?
We’re looking for a Lead Automation Expert to help both deploy and improve Gigaton’s control and optimisation products in heavy industry
You’ll be based in London, hybrid with three days a week in the office, plus regular travel to plants. We’re a Series A company of 30+ people. We raised $26M in a round led by Plural, alongside 2150, Semapa Next and Planet A Ventures.
In the near term, this is a hands-on role. You’ll work closely with Solutions Engineers, ML Engineers, Product and customer teams to get systems live in plants, solve integration and commissioning problems, and make sure our products are technically robust and trusted in production.
But the role is bigger than delivery alone. Alongside that work, you’ll help improve the product, tooling and deployment processes so that each deployment becomes faster, safer and more repeatable than the last.
Over time, the role grows from delivering great automation work on individual deployments and products to helping build Gigaton’s automation capability as a function.
We don’t draw a specific line between engineering and research teams. We operate as one cohesive unit, sharing tech stack, knowledge, and objectives. Our focus spans fundamental ML research to commercial-grade software development, offering diverse learning and impact opportunities.