Founding Engineer at C3
- Location
- Cambridge, United Kingdom
- Compensation
- Not Disclosed + Equity
C3 is solving the "impossible" infrastructure problem of building a unified GPU compute network across every cloud provider. As a Founding Engineer in Cambridge, you'll build the machine layer that powers automated research at scale—working with Firecracker microVMs, sub-second snapshot restores, and planet-scale scheduling.
If you have deep systems expertise in Linux internals, CUDA, and virtualization, this is your chance to join an elite team at the ground floor with meaningful equity. Help us build the infrastructure that lets AI agents burst compute across the globe.
What's the next step?
C3 are hiring from Jack's network. Talk to Jack for free and get a direct introduction to the team, if a good fit.
Role overview
Join C3 as a founding engineer to build the core infrastructure layer for a global GPU compute network. You will develop low-latency isolation using microVMs, implement sub-second snapshot/restore capabilities, and architect a planet-scale scheduler. This role is pivotal in enabling the next generation of automated, agent-led scientific research by providing burstable, cross-cloud compute capacity.
About C3
The next breakthroughs in cancer, fusion energy and our understanding of the universe will be found on GPUs running experiments at massive scale. The agents running these experiments need GPUs in bursts no single cloud can supply. C3 turns the world’s fragmented GPU capacity into one network they can use: describe a job once, and C3 finds GPUs, reproduces the environment, positions the data, routes the work and meters only running time. C3 is building the infrastructure layer for automated research.
What you will do
- Build microVM-isolated GPU execution environments using Firecracker or Cloud Hypervisor with GPU passthrough to run untrusted agent code safely and efficiently.
- Develop high-performance snapshot and restore mechanisms for entire machine states to ensure jobs land on warm GPUs in seconds across any cloud provider.
- Architect a cross-cloud scheduler that manages thousands of short-lived agent jobs based on capacity, price, reliability, and data proximity with fair-share queueing.
Who this is a fit for
- Has 3+ years of systems engineering experience with deep expertise in Linux internals, GPU drivers, the CUDA stack, and high-performance virtualization.
- Possesses production-level experience with job schedulers like Slurm or Kubernetes internals and has built distributed systems that scale across independent cloud regions.
- Demonstrates high AI leverage through custom agentic workflows they have built and maintained to significantly multiply their own engineering and research output.
Why this role is remarkable
- Shape the fundamental architecture of a unified global GPU network as one of the company’s first engineering hires with a path to technical leadership.
- Solve complex infrastructure problems involving Firecracker microVMs, GPU passthrough, and cross-cloud exactly-once coordination to power the future of automated research.
- Work in an environment that prioritizes high-leverage engineering, where you will build the very agentic workflows and systems that multiply your own output.
How Jack & Jill work together
What happens next?
Jack’s an AI agent for job searching and career coaching. He works for you.
Jill is the AI recruiter working for the company. She recruits from Jack’s network.
If your profile’s a match and C3 wants to meet, Jill will make the intro. In the meantime, Jack will send you excellent alternatives.