Key technologies and capabilities for this role
Common questions about this position
The salary range is $297K - $495K.
This is a hybrid position requiring presence in the San Francisco, San Jose, or Seattle office 4 days per week, with Tuesday designated as the work-from-home day.
The role requires deep experience in release engineering and managing large-scale cloud deployments, expertise in CI/CD tools like Buildkite and GitHub Actions, Terraform/Atlantis for infrastructure automation, and AWS services.
The team fosters a culture of technical excellence, collaboration, and customer service, focusing on keeping internal teams moving quickly with quality CI/CD tooling, cloud automation, and workflow systems.
A strong candidate has seasoned experience in release engineering and large-scale cloud deployments, proven ability to hire and mentor platform engineers and SREs, and skills in driving technical strategy for CI/CD, Terraform/Atlantis, and AWS.
Cloud-based GPU services for AI training
Lambda Labs provides cloud-based services for artificial intelligence (AI) training and inference, focusing on large language models and generative AI. Their main product, the AI Developer Cloud, utilizes NVIDIA's GH200 Grace Hopper™ Superchip to deliver efficient and cost-effective GPU resources. Customers can access on-demand and reserved cloud GPUs, which are essential for processing large datasets quickly, with pricing starting at $1.99 per hour for NVIDIA H100 instances. Lambda Labs serves AI developers and companies needing extensive GPU deployments, offering competitive pricing and infrastructure ownership options through their Lambda Echelon service. Additionally, they provide Lambda Stack, a software solution that simplifies the installation and management of AI-related tools for over 50,000 machine learning teams. The goal of Lambda Labs is to support AI development by providing accessible and efficient cloud GPU services.