Quick overview
Job description
About the Role
Join an AI infrastructure team to lead deployments of machine learning software in enterprise customer environments, from cloud VPCs to on-premises infrastructure. You will work directly with customer engineering, IT, security, and platform teams to make complex deployments reliable and repeatable.
What You'll Do
Plan, configure, test, and roll out deployments across customer VPC and on-premises environments.
Partner with customer engineers and senior stakeholders, including through live calls and shared communication channels.
Diagnose and resolve customer-specific Kubernetes, cloud IAM, and networking issues.
Build monitoring, telemetry, and automation that turn one-off deployment work into reusable patterns.
Understand the hardware supporting machine learning models and deploy them on customer-controlled infrastructure.
What We're Looking For
At least 3 years of experience in infrastructure engineering, DevOps, or SRE, with relevant experience in the 3 to 10+ year range.
Deep production expertise with Kubernetes and Terraform, plus experience with AWS, GCP, or Azure, networking, and infrastructure as code.
Familiarity with Python, Helm, Docker, Linux, GPU infrastructure, and customer deployment tools such as Replicated or KOTS.
Experience deploying software into customer-controlled environments, such as BYOC or VPC, air-gapped systems, on-premises installations, or customer-managed clusters.
Clear, structured communication and the ability to troubleshoot live with external engineering teams.
Infrastructure experience at a startup or high-growth technology company, with a strong record of delivery and sustained role tenure.
Compensation & Benefits
Base salary: $200,000 to $300,000 annually. Visa sponsorship is available.
Location
On-site in San Francisco, California, United States.
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