About the Role
Build and operate the infrastructure that supports research and engineering teams working on biomedical AI. As an early hire, you will establish the platform foundations for model training, inference, and data workflows, while shaping how the systems scale.
What You'll Do
Design, build, and operate cloud and GPU infrastructure for training and serving large models.
Develop platform capabilities for orchestration, job scheduling, CI/CD, developer environments, and internal tooling.
Own reliability, observability, security, and cost optimization across compute and data systems.
Partner with researchers and ML engineers to identify and resolve infrastructure bottlenecks.
Establish infrastructure-as-code practices and operational standards.
What We're Looking For
5 to 10+ years of experience in platform engineering, infrastructure, or site reliability engineering, including experience in a high-growth startup or strong engineering organization.
Hands-on experience with AWS or GCP, Kubernetes, and infrastructure-as-code tools such as Terraform.
Strong programming skills in Python and/or Go.
Experience operating ML infrastructure, including GPU clusters, distributed training, and large-scale data pipelines.
Comfort taking ownership and making technical decisions in an early-stage environment.
Compensation & Benefits
Visa sponsorship is not available for this role.
Location
On-site in San Francisco, California, United States. Candidates should be based in or willing to relocate to San Francisco.