Machine Learning Engineer

<p style="min-height:1.5em">At Gigaton, we’re on a mission to cut <strong>gigatonnes</strong> of carbon emissions from the world’s biggest emitting industries (like cement, steel and glass), by building autonomous AI control and optimisation systems that learn and leverage the physics of manufacturing. Our products run heavy industrial plants more efficiently, more stably, and with lower emissions in real time - laying the foundation for the next industrial revolution.</p><p style="min-height:1.5em">We are a team of scientists, engineers, builders, and operators who love hard problems, have high standards, and want to make change happen in the physical world. 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.</p><p style="min-height:1.5em">With Gigaton, you’ll solve really tough problems in places few people ever get close to, and build something that <em>actually</em> helps the planet. Are you up for the challenge?</p><p style="min-height:1.5em">We are seeking a Machine Learning Engineer (ranging from mid to principal) to help build the models that underpin these control systems and help us level up our machine learning infrastructure.</p><p style="min-height:1.5em">Whether in research or deployment focussed teams, we operate as one cohesive unit, sharing tech stack, knowledge, and objectives. Our focus spans from fundamental ML research to commercial-grade software development, offering diverse learning and impact opportunities.<br /></p><h2><strong>Your main responsibilities</strong></h2><p style="min-height:1.5em">Reporting to a Machine Learning Team Lead, you will:</p><ul style="min-height:1.5em"><li><p style="min-height:1.5em">Build state-of-the art systems which combine edge control with active learning algorithms to continuously deliver impact and reduce CO2 emissions.</p></li><li><p style="min-height:1.5em">Work in the machine learning team as an individual contributor, building, testing and deploying our models, optimisers and controllers.</p></li><li><p style="min-height:1.5em">Contribute to technical innovation and problem-solving across the machine learning lifecycle.</p></li><li><p style="min-height:1.5em">Collaborate with cross-functional teams on customer projects, planning, designing and delivering the work packages required, as well as playing a significant role in the development of our product.</p></li><li><p style="min-height:1.5em">Help establish best practices to improve our internal processes.</p></li><li><p style="min-height:1.5em">Contribute to the design and implementation of robust, maintainable and scalable machine learning systems.</p></li></ul><p style="min-height:1.5em">You will also contribute to our <a target="_blank" rel="noopener noreferrer nofollow" href="https://jvns.ca/blog/2014/12/21/fear-makes-you-a-worse-programmer/"><strong>fear-free</strong></a> development process by building tooling that helps the team move faster and more sustainably. You will be supported by continuous builds, tests, a constructive review system, and a strong culture of improving engineering processes.<br /></p><h2><strong>What a great fit looks like</strong></h2><ul style="min-height:1.5em"><li><p style="min-height:1.5em">You have 2 or more years of experience as a machine learning engineer.</p></li><li><p style="min-height:1.5em">