Research Engineer, Sandboxes

The Role

As a Research Software Engineer on the Sandboxes team, you will design, build, and operate the platform that runs isolated environments for untrusted code at massive scale. Our work spans distributed systems, low-level virtualization, and product-minded platform design. Engineers on this team move between deep infrastructure work and understanding how researchers actually use the platform.

This is a software engineering role, not an ML research role. You do not need prior ML experience; what matters is writing clean, reliable systems code that scales. You will join a small, senior team where the wrong hire is worse than no hire.

What You Will Do

• Design, build, and operate the sandboxing platform that runs untrusted code at scale across multiple Kubernetes clusters, from our own bare metal data centers to hyperscalers.

• Develop the sandbox runtime leveraging Firecracker, enabling fast startup, snapshotting, and efficient scheduling without blocking expensive hardware.

• Obsess over performance and latency optimisation allowing us to reach millions of concurrent sandboxes.

• Write robust, well-tested systems code in Rust and Python; review code, CI/CD, and observability across the platform.

• Own cross-cluster networking, security boundaries, isolation guarantees and monitoring for suspicious activity.

• Collaborate with researchers and ML engineers who use sandboxes for synthetic data generation and RL training, turning their needs into platform features.

• A strong background in software engineering and distributed systems, with experience building and operating large-scale infrastructure.

• Deep expertise in at least one of: Kubernetes and cluster operations, cross-cluster networking, observability, or low-level virtualization.

• Fluency in Python or Rust; comfortable writing systems code where performance and security matter.

• Strong software-design instincts: modular code, testing, CI/CD, observability, and a bias for reliability.

• A self-starter who learns fast. Core skills matter more than specific tools — we value meta-learning ability and motivation highly.

• Low-ego, collaborative, and comfortable with ambiguity in a small, high-ownership team.

Nice to have

• Experience with Firecracker, microVMs, or similar virtualization technologies.

• Product-mindedness: understanding of how sandboxes are used for synthetic data generation or RL training.

• Experience with GPU clusters, CUDA, or ML workloads.

• Prior SRE or platform engineering experience at scale.

• Open-source contributions or widely used internal tools.