Member of Technical Staff - Clusters

Sail Research; San Francisco (CA); On-site; USD 140,000 - 210,000; Full time

Benefits offered by this job

SF office

Free meals

Studio Display at desk

Job summary

Sail Research is building the world’s most efficient software for inference and agent hosting, with a focus on scalable cluster infrastructure. You’ll join as an early engineer on Clusters, writing code to provision and manage large fleets of compute across clouds.

You’ll design and implement highly available systems and scheduling to maximize GPU utilization, while steering future directions for autonomous remediation and self-serve ops.

Qualifications

• Deep understanding of Kubernetes and related technology.
• You take a product-focused approach to platform work and care deeply about building solutions that are robust, scalable, and ergonomic for users.

Responsibilities

• Build reliable systems that let us manage and share compute across clouds.
• Implement scheduling algorithms that maximize GPU utilization.
• Design highly-available systems that route around hardware faults and swap in hot spares to deliver users a pristine experience on unreliable hardware.
• Implement wraparound monitoring and alerting to ensure high availability.
• Own future directions for Clusters (autonomous remediation, self-serve ops, bare-metal provisioning, etc.).

Skills

Kubernetes

Cluster management

Tools

k3k

vCluster

Job description

Sail builds the world's most efficient software for inference (processing LLM tokens) and agent hosting (cloud VMs). Together, our technologies allow our customers to deploy AI agents at extreme scale for their most ambitious work.

In this role, you'll focus on our clusters and associated infrastructure. You’ll be an early engineer on a rapidly growing product-line and write code that automatically provisions and manages large fleets of compute.

What you’ll do

• Build a reliable systems that let us manage and share compute across clouds

• Implement scheduling algorithms that maximize GPU utilization

• Design and implement highly-available systems that route around hardware faults and swap in hot spares to deliver users are pristine experience on unreliable hardware

• Implement wraparound monitoring and altering to ensure high availability

• Own future directions for Clusters (fully autonomous remediation, self-serve ops, bare-metal provisioning, etc.).

What we’re looking for

• Deep understanding of Kubernetes and related technology.

• You take a product-focused approach to platform work and care deeply about building solutions that are robust, scalable, and ergonomic for users.

• Bonus: experience with cluster virtualization technology like k3k or vCluster.

Interview process

1. Meet the CTO, who will ask about your experience and share as much detail about Sail as you want to hear.

2. Meet an engineer on Clusters team, and talk about the problems they work on. This will also be an opportunity to ask any questions about the Sailbox product and team.

3. Come in to Sail's SF office for an interview day. Meet the whole team, then you'll have 3-4 hours to design and implement a solution to a problem that closely simulates the work we do daily. AI assistance is highly encouraged, and we'll provide a laptop with all the best tools set up. Finish with a short presentation describing your process, learnings, and results.

4. Offer. Once the team decides we want to work with you, we make a strong offer quickly and will be quite persistent over email/text/calls :)

Life at Sail

We work out of a beautiful, sunny office in downtown San Francisco. All meals are on us (and actually great; SF is a food paradise and it would be a shame to eat only bowl slop). Everyone gets a Studio Display at their desk. We are serious about investing in anything that saves us time or energy. There are six different ways to make coffee or tea in the office. A friendly (hypoallergenic) black cat named Coco visits occasionally.