Team Lead, GPU Sandboxes
Full-time
Posted on Nov 5, 2026
Team Lead, GPU Sandboxes
6 more properties
Location: San Francisco
Type: Full-time
Reports to: CTO
The role
You will lead the pod building Daytona's serverless GPU sandboxes: full-passthrough GPU compute with the same instant-start economics that define Daytona everywhere else. Pause, snapshot, and fork for GPU-attached workloads is a hard, partially solved problem - we have a working checkpoint/restore path, and you will take it to production. Customers use these sandboxes for agent-driven ML workloads, RL training, inference experimentation, and anything that needs a real GPU behind an API call.
This is an engineering role first. You will spend most of your week shipping code on the critical path and owning the pod’s technical direction, and you will also manage the pod: 4 senior engineers working alongside a dedicated PM. Management is part of the job, not the whole job.
What You'll Do
Own architecture and delivery for the GPU sandbox runtime as we pivot from MIG-based sandboxes on our H100 fleet to full VFIO passthrough: KVM/QEMU device passthrough, IOMMU isolation, driver lifecycle, and guest image management
Drive fleet efficiency: bin-packing, cold-start latency, GPU utilization, and the economics of serverless GPU (idle cost is the enemy)
Own reliability and security posture for multi-tenant GPU hosts, including isolation guarantees customers can put in a security review
Work with our bare metal and cloud providers on H100-class capacity, hardware quals, and fleet expansion
Hire, grow, and unblock the pod; set the bar for engineering quality
Partner with the pod PM on roadmap, pricing inputs, and customer-facing commitments (SLAs, quotas, regions)
What We're Looking For
8+ years in systems or infrastructure engineering, 2+ years leading engineers who ship
Deep hands-on experience with Linux virtualization: KVM, QEMU, libvirt, VFIO/PCIe passthrough, IOMMU
Production experience running GPU infrastructure at fleet scale (scheduling, health, driver hell, RMA workflows)
Strong systems programming background (Go, Rust, or C/C++)
Comfort owning outcomes end to end in a fast-moving startup, including on-call for what you build
Nice to have
Experience with NVIDIA data center GPUs (H100/A100), NVML, DCGM, MIG tradeoffs
Background at a GPU cloud, hyperscaler compute team, or serverless platform
Experience serving AI agent or RL training workloads
About Daytona
Daytona is the infrastructure layer for AI agents. We provide secure, isolated, instantly available sandboxes where agents run code, use computers, and train. Our platform powers agent workloads, reinforcement learning, and developer environments for some of the largest AI companies in the world. We just raised a $60M Series B at a $1B valuation — an 8x step-up from our Series A earlier this year. We are growing fast and hiring across the board.
You can send your application directly to careers@daytona.io.
Successful candidates will be contacted for an interview. We appreciate all the applications we receive, but only those selected for an interview will be contacted.