KVM Jobs

Baseten powers mission-critical inference for leading AI companies, enabling them to bring cutting-edge models into production. We are building the platform engineers use to ship AI products, recently securing $1.5B in Series F funding. The Agent Infra team is responsible for the core virtualization layer that powers our agent sandboxes. This layer provides each agent with its own isolated microVM, capable of running code, calling tools, and maintaining state across long tasks. We are building a cloud infrastructure from the ground up, focusing on multi-tenancy and deep hardware integration.

$165k - $330k

Anthropic

Our Sandboxing team builds the isolation layer that enables Claude to run code, use computers, or act as an agent. These systems are critical for executing code written by Claude for users, training and evaluating models, and supporting customer-deployed agents. The sandboxes must start rapidly, withstand adversarial code, and scale to handle numerous concurrent sessions. This role involves working at the intersection of the Linux kernel, virtualization, and container technologies, collaborating with research, product, and security teams to ensure both safety and performance.

$320k - $485k

Together AI

Together AI is building the AI Native Cloud, an end-to-end platform for the full generative AI lifecycle, combining a fast LLM inference engine with state-of-the-art GPU cloud infrastructure. The Together Cloud team builds the flagship IaaS product that provides high-performance, AI-ready GPU clusters through a self-serve cloud console, along with the virtualized infrastructure layer powering Together's inference, RL, and fine-tuning products. As a Senior Software Engineer focusing on AI Compute, you will build and own major components of the next generation AI cloud platform – a highly available, global cloud infrastructure with cutting-edge virtualization of the latest ML hardware. This virtualized computing platform powers our own SaaS products and serves external cloud customers through self-serve offerings. The hard problems in rapidly scaling heterogeneous GPU fleets are software problems that we solve by building global and in-DC services, Kubernetes operators, and high-performance SDN libraries, forking hypervisors and Linux kernels, and building infra tailored to inference and fine-tuning. You'll own massive greenfield projects across their full lifecycle – scoping the problem, designing the system, and building it through to GA launch.

$220k - $270k