1 month ago
Base Salary
$230k - $346k/yr
Responsibilities
- Design, build, and maintain scalable control plane services, operators, custom Kubernetes controllers, and Go/Python automation for cluster provisioning, upgrades, patching, and deletion.
- Build GPU-aware orchestration systems for GPU scheduling and resource allocation.
- Develop networking solutions for AI workloads involving CNI integration, high-performance fabrics, RDMA, and GPUDirect.
- Build resilient distributed systems with failure handling, retries, backoff, timeouts, and degraded-mode operation.
- Develop inference platform services, including model serving infrastructure, inference-based autoscaling, and multi-model deployment patterns.
- Create internal tools and CLIs for ML and AI teams to deploy and monitor inference services.
- Support and debug production systems through an on-call rotation.
Requirements
- Require 6+ years of software engineering experience with ownership of significant technical scope, such as driving projects from design through production or acting as a de facto technical lead.
- Require deep understanding of Kubernetes internals, including controllers, schedulers, operators, CRDs, CSI, CNI, and extension patterns.
- Require knowledge of distributed systems fundamentals, fault tolerance, graceful degradation, and failure handling at scale.
- Require experience operating control planes and low-level components of large-scale Kubernetes clusters.
- Require experience with observability at scale, including Prometheus, Grafana, distributed tracing, and actionable alerting.
- Require strong programming skills in Go and Python.
- Require knowledge of Linux systems, networking, containers, and cloud infrastructure.
- Preferred qualifications include experience with managed Kubernetes services such as GKE, EKS, or AKS; Kubernetes control plane components; NVIDIA GPU and networking tools; Slurm or Kubernetes-native batch schedulers; GPU, InfiniBand, RDMA, or HPC systems; AI/ML storage architecture; and CNCF or Kubernetes SIG contributions.
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.
- Offers cash and equity compensation, health, dental, and vision coverage, wellness and commuter stipends for select roles, a 401(k) plan with a 2% company match for USA employees, and flexible paid time off.
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.