Machine Learning Engineer

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.

📈 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 Notion page.