Baseten

Baseten

Engineering Manager Runtime - Storage

San Francisco

Sponsorship not specifiedDetected 2 days ago
GoRustC++CCode ReviewKubernetesLinuxMachine LearningSparkPerformance ManagementCadenceResearchLeadershipCommunicationMentoring

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About the role

  • AI inference is not a general-purpose workload.
  • The tools the industry has relied on for a decade weren't built for this, and patching around those limitations at higher layers only goes so far.
  • That vertical ownership means we can fix these problems at the root.

Responsibilities

  • Provide regular coaching, feedback, and career development support to your direct reports
  • Own reliability of the delivery path as a measured outcome: end-to-end instrumentation from snapshotter initialization to first inference request, targets for cold start and cache behavior, tolerance for failing upstream registries and object stores, and safe rollout of changes to a path every customer depends on
  • Make the delivery path work across heterogeneous clusters and cloud providers, each with its own object store and network
  • Review designs and code across the area, and take on hands-on work where it unblocks the team

Requirements

  • Strong systems programming background in Go, Rust, and/or C/C++, with the ability to engage credibly in code reviews and architectural discussions
  • Strong written and verbal communication skills, with the ability to influence without authority across teams
  • Working knowledge of the Linux storage stack: filesystems, the page cache, block devices, and mounts
  • If you've managed systems engineers and have hands-on experience with caching, content-addressable storage, or distributed filesystems, we'd love to talk.

Nice to have

  • Contributions to containerd/containerd, snapshotter projects (stargz, soci, nydus, overlaybd), distribution/distribution, or closely related open-source projects
  • Familiarity with lazy-loading snapshotters or peer-to-peer image distribution
  • Experience with EROFS, FUSE, ublk, or io_uring
  • Experience running storage services on Kubernetes

Compensation

  • Competitive compensation, including meaningful equity

Benefits

  • Competitive compensation, including meaningful equity
  • (U.S. only) 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
  • Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.
  • If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you.
  • Own on-call health for the team's services, including escalation paths and follow-through on incidents

Company info

  • Champion the team's contributions back to containerd and the snapshotter ecosystem alongside the maintainers on the Runtime Fabric team
  • Act as the point of contact for storage across Baseten, ensuring model deployment, training, and platform teams have the integration support they need
  • Optimize requirements for the underlying storage platforms with the infrastructure team: object storage, local NVMe and block storage, and network bandwidth per cluster, so that capacity and provider decisions account for what the delivery path needs
  • Work with the head of Runtime Fabric and product stakeholders to prioritize storage investments based on customer impact and infrastructure reliability
  • Communicate team progress, technical trade-offs, and incidents clearly to the team and to leadership
  • Shape storage products tailored to Baseten's workloads: extend BDN from model weights to container images, training checkpoints, and deployment artifacts, and define the interfaces that model deployment, training, and customers use to reach them
  • At Baseten, we are committed to fostering a diverse and inclusive workplace.
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