gigaton - Machine Learning Engineer

• Reporting to a Machine Learning Team Lead, you will: • Build state-of-the art systems which combine edge control with active learning algorithms to continuously deliver impact and reduce CO2 emissions. • Work in the machine learning team as an individual contributor, building, testing and deploying our models, optimisers and controllers. • Contribute to technical innovation and problem-solving across the machine learning lifecycle. • 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. • Help establish best practices to improve our internal processes. • Contribute to the design and implementation of robust, maintainable and scalable machine learning systems. • You will also contribute to our fear-free https://jvns.ca/blog/2014/12/21/fear-makes-you-a-worse-programmer/ 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. • WHAT A GREAT FIT LOOKS LIKE • You have 2 or more years of experience as a machine learning engineer. • You are familiar with ML techniques, and have both theoretical ML knowledge and experience implementing different types of solutions. • You are proficient in Python and have a good understanding of the ecosystem of tools and libraries that support ML development (e.g., scikit-learn, PyTorch). • You have experience working in end-to-end machine learning deployments. • You have experience working in a scientific environment across disciplines (particularly physics, chemistry, materials science, and engineering), either through previous roles or study. • Are passionate about making a positive impact on climate change mitigation and possess a strong interest in our mission. • YOU’LL EXCEL IF • You have experience in any of: control systems, time-series modelling, reinforcement learning, system identification, optimisation or bayesian statistics. • You are used to working in a fast-paced startup environment with an agile process. • You have a degree in machine learning, physics, chemistry, engineering, mathematics or computer science. • You have a track record of developing novel ML methods in relevant fields. • You are hungry for responsibility, enthusiastic about taking on the design and development of solutions to difficult problems, and eager to drive the progress of new products. • You have a solid understanding of modern cloud compute infrastructure as it relates to machine learning, and experience in working with AWS, GCP, Azure, or other vendors. • You have have designed and built systems end to end with software architectural best practice. • In return for your hard work, we’ll give you • 📈 Equity in the company: When we win, you win. You’ll get share options, so you’re part of our journey from the inside. • 🕰️ Flexible working We trust you to know how and when you work best and to work that out with your team. • 🌴 30 days of holiday (plus bank holidays). Rest is productive. Take the time you need to recharge • 🪙 A generous pension scheme. We’re planning for the future in more ways than one. • Our Operating Principles • ↗️ Go Gig or Go Home: High Bar, All In. What we do matters to humanity, to our customers and to each other. We hold ourselves to an extraordinarily high bar and bring the urgency this mission requires. • 🏭 Concrete Honesty: Be honest. As concrete forms the foundation of our world, genuine honesty and transparency are the bedrock of our culture. • 🦾 Autonomous Ownership: High agency, high ownership. We build systems that take control and make things better. We do the same: see it, own it, drive it. • 😄 Cement it with Kindness & Fun: Have fun, be kind. We're here to extend Earth's life, but ours is still limited. We want to enjoy the ride. To see these in full, go to Gigaton’s Operating Principles https://gigaton-technologies.notion.site/gigaton-s-operating-principles Notion page.