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calicolabs
South San Francisco, CA
Source: calicolabs careers · View original posting
From calicolabs's posting. “We” and “our” refer to the employer.
Calico (Calico Life Sciences LLC) is an Alphabet-founded research and development company whose mission is to harness advanced technologies and model systems to increase our understanding of the biology that controls human aging. Calico will use that knowledge to devise interventions that enable people to lead longer and healthier lives.
Calico’s highly innovative technology labs, its commitment to curiosity-driven discovery science and, with academic and industry partners, its vibrant drug-development pipeline, together create an inspiring and exciting place to catalyze and enable medical breakthroughs.
Calico seeks a Senior / Staff Cloud Engineer to lead the execution and operation of our next-generation machine learning (ML) platform. As the technical authority for our Google Cloud Platform (GCP) environment, you will build infrastructure-as-Code (IaC), design secure perimeters, automate identity management, and migrate existing workflows into a unified, compliant infrastructure.
If you are passionate about DevSecOps, IaC, and building "paved paths" that empower scientists while enforcing rigorous security, this is the role for you. You will be the critical bridge that allows our ML Systems and Research engineers to train and deploy ML models for frontier BioML research.
Please note: No biology or life sciences background is required for this role.
You will work with a team of researchers and engineers on Calico’s key strategic cross-functional initiatives through the following responsibilities:
Deliver our next-generation ML platform
Lead the consolidation and modernization of our compute environments, and accelerate the whole company's R&D cycle
Lead the centralization of GCP projects into a unified, compliant landing zone
Design secure perimeters to protect sensitive biological data, and build automated guardrails using Terraform
Design, deploy, and maintain robust GKE clusters tailored for distributed ML training and batch processing workloads
Troubleshoot node-level GPU/TPU issues, manage scheduling add-ons, and optimize cluster autoscaling
Design intuitive onboarding processes and "paved paths" for scientists to seamlessly onboard onto the new platform
Manage org-level GPU/TPU compute capacity, implement centralized billing and cost reporting, and build comprehensive monitoring dashboards to track cluster utilization and optimize R&D expenditure
The estimated base salary range for this role is $220,000 - $290,000. Actual pay will be based on a number of factors including experience and qualifications. This position is also eligible for two annual cash bonuses.
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