Senior Kubernetes Operations Engineer @ Lambda

Lambda’s GPU cloud is used by deep learning engineers at Stanford, Berkeley, and Carnegie Mellon. Lambda’s on-prem systems power research and engineering at Intel, Microsoft, Kaiser Permanente, major universities, and the Department of Defense.

If you’d like to build the world’s best deep learning cloud, join us.

What You’ll Do

Remotely install, upgrade, operate and maintain bare-metal Kubernetes clusters (up to thousands of nodes each)
Handle cluster degradation, recovery and resizing using our fleet management tooling
Perform out-of-hours on-call response for critical incidents as part of a well-balanced on-call rotation
Work on improving our tooling, automation, and processes, for both daily operations, alerting, and incident response
Dive into systems at a low level to solve unique cluster problems and write up your findings
Assist customers with high-level Kubernetes questions and integration with applications, storage and authentication
Assist with initial cluster build-outs and validation to help identify failed hardware before customer delivery
Work closely with our HPC Ops and Datacenter Ops teams on issues that require lower-level expertise or cross-functional solutions
Mentor and assist less-experienced team members
Have a voice in our product direction and help us think about how to minimize operational costs and complexity

You

Are an experienced operations engineer, SRE, sysadmin or similar with a deep knowledge of running Linux clusters and systems
Are very familiar with running on bare-metal (including knowledge of BMCs, kernel drivers, PXE, RAID, VLANs, hypervisors)
Have a good understanding of containers, virtualisation, and the mechanisms underpinning them
Have a good understanding of daily operation, bug-fixing and maintenance of Kubernetes
Have experience in an on-call environment and with incident response
Can perform incident post-mortems and develop procedures and tooling to prevent root causes from reoccurring
Have an excellent ability to learn on-the-fly and adapt to solve problems
Are able to work either independently with limited direction, or as part of a team
Are able to work with customers during incidents either via tickets, live messaging, or as part of a larger call.

Nice to Have

Deep Kubernetes experience
Experience with user-level restrictions and hardening (e.g. AppArmor)
Experience with network engineering
Experience with HPC clusters, environments & tooling
Experience with large-scale AI/ML training clusters
Experience with machine learning/AI frameworks
A passion for running your own bare-metal lab

Salary Range Information

Based on market data and other factors, the salary range for this position is approximately £135,200 - £194,400. However, a salary higher or lower than this range may be appropriate for a candidate whose qualifications differ meaningfully from those listed in the job description.

About Lambda

We offer generous cash & equity compensation
Investors include Gradient Ventures, Google’s AI-focused venture fund
We are experiencing extremely high demand for our systems, with quarter over quarter, year over year profitability
Our research papers have been accepted into top machine learning and graphics conferences, including NeurIPS, ICCV, SIGGRAPH, and TOG
We have a wildly talented team of 300, and growing fast
Health, dental, and vision coverage for you and your dependents
Commuter/Work from home stipends for select roles
401k Plan with 2% company match
Flexible Paid Time Off Plan that we all actually use

A Final Note:

You do not need to match all of the listed expectations to apply for this position. We are committed to building a team with a variety of backgrounds, experiences, and skills.

Equal Opportunity Employer

Lambda is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law.

Compensation Overview

6 month growth

1 year growth

2 year growth

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