Engineering Manager, Runtime Fabric

Details

• Recruit, hire, and develop a high-performing team of systems engineers with deep container and Linux expertise.
• Foster a culture of technical rigor, open-source contribution, and continuous improvement.
• Provide regular coaching, feedback, and career development support to your direct reports.
• Partner with engineering leadership to define the long-term vision and roadmap for container runtime and storage infrastructure.
• Guide the team in extending and hardening containerd, runc, and related OCI ecosystem projects to meet the GPU-specific requirements of production AI inference, including startup performance, GPU device access, and multi-tenant isolation.
• Oversee the architecture and evolution of the Baseten Delivery Network: the tiered caching and weight delivery system that makes cold starts 2–3x faster and eliminates thundering herd failures during burst scaling events.
• Drive the expansion of BDN's architecture, currently focused on model weights, to container images, training checkpoints, and deployment artifacts.
• Provide technical oversight on GPU-aware isolation mechanisms for multi-tenant inference, including secure container runtimes, Linux namespace hardening, and longer-term micro-VM integration.
• Ensure the team maintains end-to-end ownership of the container startup performance path, from snapshotter initialization through weight delivery to first inference request.
• Champion the team's contributions back to the open-source containerd ecosystem alongside a team of core maintainers.
• Act as the primary advocate for Runtime Fabrics across the organization, ensuring upstream and downstream teams have the integration support they need.
• Collaborate with product and engineering stakeholders to prioritize investments based on business impact and infrastructure reliability.
• Communicate team progress, technical trade-offs, and architectural decisions clearly to leadership.
• Proven experience managing and growing engineering teams in a systems, infrastructure, or low-level runtime context.
• Deep familiarity with the Linux container ecosystem: containerd, runc, OCI Runtime Spec, Linux namespaces, and cgroups, with the ability to engage credibly in code reviews and architectural discussions.
• Contributions to containerd/containerd, opencontainers/runc, google/gvisor, kata-containers/kata-containers, or closely related open-source projects.
• Strong systems programming background in Go and/or C/C++.
• Experience with distributed storage systems, content-addressable storage, or large-scale caching infrastructure.
• Understanding of how container images are structured, stored, and delivered at scale.
• Strong written and verbal communication skills, with the ability to influence without authority across teams.
• Experience with GPU device access in containers: NVIDIA Container Toolkit, CDI (Container Device Interface), or GPU-aware scheduling.
• Familiarity with lazy-loading snapshotters (stargz, soci, EROFS/Nydus) or peer-to-peer image distribution.
• Experience with secure container runtimes (gVisor, Sysbox) or micro-VM technologies (Firecracker, Cloud Hypervisor).
• Understanding of containerd's shim API (v2) and experience building custom shim implementations.
• Background in multi-tenant infrastructure or security-sensitive serving environments.
• Competitive compensation, including meaningful equity.
• 100% coverage of medical, dental, and vision insurance for employee and dependents
• Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!)
• Paid parental leave
• Fertility and family-building stipend through Carrot
• Company-facilitated 401(k)
• Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.