Senior Site Reliability Engineer - Managed Kubernetes

We're here to help the smartest minds on the planet build Superintelligence. The labs pushing the edge? They run on Lambda. Our gear trains and serves their models, our infrastructure scales with them, and we move fast to keep up. If you want to work on massive, world-changing AI deployments with people who love action and hard problems, we're the place to be.

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

What You’ll Do

• Operate and maintain bare-metal Kubernetes clusters, scaling up to thousands of nodes

• Handle cluster degradation, recovery, resizing, and incident response using fleet management tools

• Participate in a well-managed on-call rotation for critical incidents

• Assist customers with Kubernetes questions, workload integration, storage, and authentication

• Work closely with our HPC Ops and Datacenter Ops teams for low-level or cross-functional issues

• Use Python and Golang to create tooling and automate the validation of platform quality.

• Design, build, and maintain scalable control plane services, operators, and custom controllers for Kubernetes

• Develop automation for cluster lifecycle management: provisioning, upgrades, patching, and deletion.

• Define and implement SLOs and SLIs for Kubernetes services, workloads, and platform reliability.

About You

Must-Have

• 6+ years of experience in a SRE, operations engineer, or similar role, with a deep knowledge of running Linux clusters and systems

• Strong programming skills in Go and Python; experience with GitOps (e.g., ArgoCD), Helm, and Kubernetes operators

• Proven experience operating Kubernetes clusters in production environments (on-prem, EKS, GKE, or similar)

• Can work either independently with limited direction or as part of a team

• Can work with customers during incidents either via tickets, live messaging, or as part of a larger call.

• Familiarity with observability tools like Prometheus, Grafana, FluentBit, and CI/CD pipelines

• Proven experience provisioning Kubernetes using tools such as kubeadm, Cluster API, or similar

Nice-to-Have

• Deep Kubernetes expertise: CRDs, CSI, CNI, Kubernetes Operator Coding experience

• Exposure to HPC clusters, AI/ML workloads, or large-scale GPU clusters

• Hybrid or multi-cloud Kubernetes environment experience

• Contributions to CNCF projects or Kubernetes SIGs

Why Join Us

• Work on cutting-edge Managed Kubernetes platforms for AI/ML workloads

• Influence the platform roadmap and help shape operations and reliability best practices

• Collaborate with a highly skilled engineer

• Opportunity to mentor and grow within a fast-growing, technology-driven environment

About Lambda

• Founded in 2012, ~400 employees (2025) and growing fast

• We offer generous cash & equity compensation

• Our investors include Andra Capital, SGW, Andrej Karpathy, ARK Invest, Fincadia Advisors, G Squared, In-Q-Tel (IQT), KHK & Partners, NVIDIA, Pegatron, Supermicro, Wistron, Wiwynn, US Innovative Technology, Gradient Ventures, Mercato Partners, SVB, 1517, Crescent Cove.

• 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

• Health, dental, and vision coverage for you and your dependents

• Wellness and Commuter stipends for select roles

• 401k Plan with 2% company match (USA employees)

• 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.