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
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Plan, configure, test, and roll out deployments across customer VPC and on-premises environments.
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Partner with customer engineers and senior stakeholders, including through live calls and shared communication channels.
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Diagnose and resolve customer-specific Kubernetes, cloud IAM, and networking issues.
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Build monitoring, telemetry, and automation that turn one-off deployment work into reusable patterns.
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Understand the hardware supporting machine learning models and deploy them on customer-controlled infrastructure.
What We're Looking For
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At least 3 years of experience in infrastructure engineering, DevOps, or SRE, with relevant experience in the 3 to 10+ year range.
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Deep production expertise with Kubernetes and Terraform, plus experience with AWS, GCP, or Azure, networking, and infrastructure as code.
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Familiarity with Python, Helm, Docker, Linux, GPU infrastructure, and customer deployment tools such as Replicated or KOTS.
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Experience deploying software into customer-controlled environments, such as BYOC or VPC, air-gapped systems, on-premises installations, or customer-managed clusters.
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Clear, structured communication and the ability to troubleshoot live with external engineering teams.
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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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