1 month ago
Base Salary
$314k - $465k/yr
Responsibilities
- Drive the technical vision for Lambda’s bare-metal Managed Kubernetes platform, including control-plane scalability, multi-tenancy, cluster lifecycle management, and high availability.
- Build GPU-aware orchestration systems and integrate NVIDIA technologies for GPU scheduling, networking, topology awareness, and performance.
- Develop Managed Slurm on Kubernetes and higher-level inference services, including model serving, autoscaling, and multi-model deployment.
- Define requirements spanning compute, networking, storage, security, bare-metal provisioning, and network topology for managed infrastructure services.
- Design self-healing, resilient platforms with incident-response automation, root-cause analysis, upgrade automation, security patching, and zero-downtime maintenance.
- Lead chaos engineering, observability, operational excellence, and reliability initiatives for managed services.
- Set technical direction, lead design reviews, mentor engineers, influence roadmaps, and establish Kubernetes and distributed-systems best practices.
- Collaborate with Network, Storage, Security, Customer Success, NVIDIA, open-source communities, customers, and internal teams.
- Represent Lambda through technical writing, conference talks, strategic customer engagements, and contributions to the AIOps vision.
Requirements
- 10+ years of experience in software engineering, platform engineering, or SRE, including at least 5 years focused on Kubernetes at scale.
- Expert understanding of Kubernetes internals, including API machinery, controllers, schedulers, operators, CRDs, CSI, CNI, and extension patterns.
- Holistic expertise across compute, networking, storage, and security, with the ability to design full-stack infrastructure solutions.
- Strong production software engineering skills in Go and Python.
- Deep experience with GPU orchestration in Kubernetes, including NVIDIA GPU Operator, device plugins, DCGM, MIG, time-slicing, and GPU-aware scheduling.
- Proven technical leadership in cross-team design decisions, mentoring, and infrastructure direction.
- Experience designing and operating managed services or multi-tenant platforms for external customers.
- Strong understanding of distributed-systems principles, including consensus, fault tolerance, consistency models, and graceful degradation.
- Experience with observability at scale, including Prometheus, Grafana, distributed tracing, and actionable alerting.
- Solid Linux and L2-L7 networking knowledge, including RDMA, InfiniBand, and RoCE.
- Experience with infrastructure-as-code and GitOps workflows.
- Preferred: experience with managed Kubernetes services such as GKE, EKS, or AKS, or Kubernetes control-plane components.
- Preferred: experience with NVIDIA Network Operator, NCCL tuning, Topograph, AICR, HPC, Slurm, KAI, Volcano, Kueue, confidential computing, customer migrations, CNCF or Kubernetes projects, security and compliance in multi-tenant environments, or ML infrastructure.
Benefits
- The role requires working from the San Francisco, San Jose, or Bellevue office four days per week, with Tuesday designated as the work-from-home day.
- Generous cash and equity compensation is offered, but no specific salary amount is stated.
- Health, dental, and vision coverage are provided for employees and dependents.
- Wellness and commuter stipends are available for select roles.
- 401(k) plan with a 2% company match is available to USA employees.
- Flexible paid time off plan.
Tech Stack
Categories
About Lambda
Lambda provides GPU cloud computing and on-prem AI hardware—servers, clusters, and workstations—for teams training and serving large ML models. Its products include NVIDIA H100/A100 instances, managed clusters, and the Lambda Stack software, sold via usage-based cloud pricing and hardware sales. Founded in 2012 and headquartered in San Francisco, the privately held company serves researchers, startups, enterprises, and hyperscalers.