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Hiring / Founding Engineer

Founding Engineer

Build the grid for compute

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.

C3 is turning fragmented GPU compute supply into a single global network, creating the compute infrastructure layer for autoresearch at scale. If you want to work on the hardest problems in GPU computing, across hardware, distributed systems and ML research, this is an opportunity to get in early and help shape an extremely technical business. If you have 3+ years of engineering experience shipping code (exceptional open-source work counts), or can demonstrate excellence in physics, maths, computer science or a related technical field, please reach out.

Autoresearch at scale.

C3 is building the infrastructure for Karpathy-style autoresearch at scale: agents that propose, run and score experiments around the clock, each placed on the right GPU in any cloud. Our Autoresearch service is in beta.

The hard problems

C3 is writing the operating system for the world's GPUs. Its scheduler has to reason about a planet: capacity that appears and vanishes across hundreds of suppliers, prices that move like a market, datasets too large to move quickly, and agents firing thousands of experiments in bursts. It must predict where demand will land before it arrives, and keep every job running when any cloud beneath it fails. Nobody has built this. The first version runs in production today.

The role

  • Bring every GPU cloud onto C3: provider adapters for Nebius, Crusoe, Hyperstack, GCP, AWS and the next twenty. Provisioning, images and snapshots, quotas, networking and teardown, with each cloud's quirks hidden behind one interface.
  • The job path, end to end: from c3 deploy or an agent's MCP call to a running process on a GPU. Workspace upload, environment reproduction, dataset mounts, streamed logs and artifacts back.
  • Route every job: pick the supplier from live capacity, price, performance and reliability, and fail over when one falls down.
  • The Go agent: lifecycle, mounts, log streaming, recovery and per-second metering on every machine.
  • Autoresearch at scale: the research engines (Karpathy-style agent loops, OpenEvolve, AIDE) and the service that runs them on C3.
  • The stack: Go agent and CLI; TypeScript control plane on Cloudflare Workers (Hono, D1); Python SDK; Next.js dashboard.
  • Shape C3: you'll help define what C3 becomes, with a path to senior or executive leadership.
  • Cambridge: majority in person with the founder and C3's first engineer.

Must have

  • 4+ years shipping production code to real users; strong open-source work counts.
  • Integrations that stay working: you have built and maintained many integrations against messy third-party APIs, and kept them reliable as those APIs changed.
  • Backend and cloud fundamentals: APIs, queues, retries and idempotency; Linux, containers and networking; at least one cloud provider's API in depth.
  • AI leverage. Demonstrable custom agentic workflows are required. Show us systems you built, in or out of work, and how they multiplied your output.

Success in the first three months

  • Supplier coverage from six to twenty-five on a repeatable adapter framework, about two a week, each with an end-to-end test that provisions a real GPU and runs a job.

Nice to have

  • Go and TypeScript; GPU and CUDA environments; Docker image pipelines; MCP or agent tooling; a research background in a computational field with substantial software work.

Interested, or know someone?

Write to sam@cthree.cloud with your CV and two sentences on the most interesting thing you have ever built and why it mattered. Excited by impossible infrastructure problems and shaping a company from day one? We'd love to hear from you.