About the job
At Orbital Materials, we leverage advanced AI technologies to engineer data center hardware that surpasses industry standards. Our AI capabilities simulate materials at the atomic level and evaluate millions of hardware configurations within a fraction of the time traditional methods require. This innovative approach leads to hardware with unmatched specifications: 1 MW/rack, PUE < 1.04, and 12-week lead times.
Every deployment contributes valuable field data that refines our AI models. Improved models yield superior hardware, and this cycle of continuous enhancement accelerates our advancements in AI. We are not merely observers of AI progress; we actively influence its trajectory.
Our focus on data centers is driven by the urgent market demand and stringent specifications, but our AI-driven development process, covering materials discovery, hardware design, and manufacturing optimization, extends to any complex physical system. Data centers serve as our initial testing ground, not our limit.
With operations in London, Canada, and the USA, we are expanding our teams across Machine Learning Research, Product Development, Mechanical Engineering, and Chemical Engineering. If you're eager to explore the intersection of AI and materials science, we want to connect with you.
In the role of Staff Machine Learning Researcher, you will design and implement state-of-the-art AI systems for multi-scale physical technology design. Our multi-scale approach involves creating leading foundation models that simulate both the atomic motion of materials and the macroscopic fluid dynamics in 1GW data centers. You will facilitate cross-scale co-design, utilizing the expertise of our scientists and engineers, complemented by industry-leading domain agents.
This position requires you to set high technical standards and lead projects from initial prototype stages to full production deployment. We seek a candidate who is passionate about craftsmanship, committed to continuous learning, and adept at building scalable systems. A collaborative spirit and a genuine enthusiasm for applying AI to tackle significant global industrial challenges are essential.
