Senior DevOps Engineer

About

This is a chance to build the infrastructure behind one of the more technically serious applications of AI right now - where high-performance simulation, machine learning, and real-world engineering collide.

We’re partnered with a Series B Physics AI company that is fundamentally changing how engineering teams design and iterate on products. Their platform combines high-fidelity simulation with machine learning to predict physical outcomes in real time, allowing companies across aerospace, automotive, and advanced manufacturing to move faster and make better decisions with less risk.

They’re now building out their cloud platform team and are looking for a Senior DevOps Engineer to take ownership of the infrastructure that underpins everything they do.

Role

The environment is Kubernetes-first, running across GCP and AWS, and you’ll be responsible for how that platform evolves - from cluster architecture and workload scheduling through to CI/CD, observability, Terraform and security. There’s a strong emphasis on building things properly from day one, rather than retrofitting scale later.

A big part of the role sits at the intersection of platform engineering and machine learning infrastructure. You’ll be supporting GPU-based workloads, partnering closely with research teams to optimize environments for training and inference, while also improving the broader developer experience through automation and internal tooling.

The profile that tends to do well here is someone who enjoys ownership, moves quickly without cutting corners, and is comfortable operating in a high-context, low-ego team where expectations are high but bureaucracy is low.

Compensation

Base Compensation is up to $250k base salary with meaningful equity, and the work sits right at the intersection of modern cloud infrastructure and next-generation AI.