Lambda Corporation
Lambda, The Superintelligence Cloud, builds Gigawatt-scale AI Factories for Training and Inference. Lambda's mission is to make compute as ubiquitous as electricity and give every person access to artificial intelligence. One person, one GPU.
If you'd like to build the world's best deep learning cloud, join us.
*Note: This position requires presence in our San Francisco,San Jose, or Seattle office location 4 days per week; Lambda's designated work from home day is currently Tuesday.
Engineering at Lambda is responsible for building and scaling our cloud offering. Our scope includes the Lambda website, cloud APIs and systems as well as internal tooling for system deployment, management and maintenance.
What You'll Do
Architect, deploy, and manage Kubernetes clusters across AWS, OCI, and on-prem datacenters. Build and maintain automation for cluster lifecycle management, upgrades, and scaling. Own the reliability, performance, and security of Kubernetes workloads. Implement observability, logging, and alerting for clusters and critical workloads. Partner with developers to design scalable, cloud-native services and CI/CD pipelines. Define and enforce best practices for resource usage, networking, and RBAC. Lead incident response, root cause analysis, and post-mortems for cluster-related issues. Mentor junior engineers and contribute to internal platform engineering standards. You
5+ years of experience in Platform, Infrastructure, or SRE roles. Expert knowledge of Kubernetes internals and operational practices. Proven experience running Kubernetes clusters in production at scale. Strong skills with Helm, Kustomize, or similar deployment tooling. Solid understanding of networking, service meshes, and container runtimes. Proficiency in infrastructure-as-code (Terraform, Pulumi, etc.). Experience with observability stacks (Prometheus, Grafana, ELK, OpenTelemetry). Familiarity with security best practices (network policies, secrets management, image scanning). Strong coding skills in Go, Python, or similar for automation. Comfort with GitOps workflows and CI/CD integration. Excellent problem-solving skills and ability to operate in complex environments. Nice to Have
Experience with multi-cluster, multi-cloud, or hybrid environments. Knowledge of GPU scheduling, HPC workloads, or ML/AI infrastructure. Exposure to cost optimization and capacity planning for large clusters. Contributions to CNCF or Kubernetes open-source projects. Salary Range Information
The annual salary range for this position has been set based on market data and other factors. 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
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.
If you'd like to build the world's best deep learning cloud, join us.
*Note: This position requires presence in our San Francisco,San Jose, or Seattle office location 4 days per week; Lambda's designated work from home day is currently Tuesday.
Engineering at Lambda is responsible for building and scaling our cloud offering. Our scope includes the Lambda website, cloud APIs and systems as well as internal tooling for system deployment, management and maintenance.
What You'll Do
Architect, deploy, and manage Kubernetes clusters across AWS, OCI, and on-prem datacenters. Build and maintain automation for cluster lifecycle management, upgrades, and scaling. Own the reliability, performance, and security of Kubernetes workloads. Implement observability, logging, and alerting for clusters and critical workloads. Partner with developers to design scalable, cloud-native services and CI/CD pipelines. Define and enforce best practices for resource usage, networking, and RBAC. Lead incident response, root cause analysis, and post-mortems for cluster-related issues. Mentor junior engineers and contribute to internal platform engineering standards. You
5+ years of experience in Platform, Infrastructure, or SRE roles. Expert knowledge of Kubernetes internals and operational practices. Proven experience running Kubernetes clusters in production at scale. Strong skills with Helm, Kustomize, or similar deployment tooling. Solid understanding of networking, service meshes, and container runtimes. Proficiency in infrastructure-as-code (Terraform, Pulumi, etc.). Experience with observability stacks (Prometheus, Grafana, ELK, OpenTelemetry). Familiarity with security best practices (network policies, secrets management, image scanning). Strong coding skills in Go, Python, or similar for automation. Comfort with GitOps workflows and CI/CD integration. Excellent problem-solving skills and ability to operate in complex environments. Nice to Have
Experience with multi-cluster, multi-cloud, or hybrid environments. Knowledge of GPU scheduling, HPC workloads, or ML/AI infrastructure. Exposure to cost optimization and capacity planning for large clusters. Contributions to CNCF or Kubernetes open-source projects. Salary Range Information
The annual salary range for this position has been set based on market data and other factors. 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
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.