Quick overview
Job description
About the Role
Join an AI and machine learning infrastructure team deploying production systems in enterprise customer environments, from cloud VPCs to on-premises hardware. You will partner directly with customer engineering, security, and platform teams to make complex deployments reliable and repeatable.
What You'll Do
Plan, configure, test, and roll out deployments across customer cloud and on-premises environments.
Work directly with customer IT, security, and engineering teams, including through live calls and shared communication channels.
Diagnose and resolve infrastructure issues involving Kubernetes configuration, cloud IAM, and networking.
Build monitoring, telemetry, and automation that turn deployment work into scalable, repeatable patterns.
Understand the hardware requirements of 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 generally in the 3 to 10+ year range.
Deep, production-level expertise with Kubernetes and Terraform.
Experience with cloud platforms such as AWS, GCP, or Azure, plus networking, infrastructure as code, Linux, and Docker.
Familiarity with Python, Helm, GPU infrastructure, and customer-managed deployment tools or environments such as VPC, air-gapped, and on-premises installations.
Strong communication skills and experience troubleshooting infrastructure issues live with external engineering teams.
Background in a startup or high-growth technology environment, with demonstrated ownership of core infrastructure.
Compensation & Benefits
Base salary: $200,000 to $300,000 annually. Visa sponsorship is available.
Location
On-site in San Francisco, California.
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