Platform Engineer

Description Helical is the AI-native lab for biology. We turn biological foundation models into production systems for discovery—so scientists can run experiments in silico at the speed of inference. We’re already deployed with top pharma, supporting work from target identification to biomarker discovery. The Role We’re hiring a Platform Engineer to build and scale the infrastructure behind our virtual AI lab. This is a hands-on role: debugging Kubernetes one moment, improving architecture the next, shipping to production throughout. You’ll be working on the system that makes AI-driven drug discovery actually usable at scale. What You’ll Do Run and scale Kubernetes (incl. GPU workloads) Own cloud infrastructure and infra-as-code Support ML training & inference pipelines Manage CI/CD, observability, and deployments Handle databases, storage, and migrations Build automation (Python/Bash) Work closely with ML, backend, and product What We’re Looking For 4+ years in platform / DevOps / infra Strong Kubernetes, Docker, cloud (AWS/GCP/Azure) GPU workloads / ML infra Experience designing & operating multi-tenant architectures with strict tenant isolation Familiarity with autoscaling & service isolation Experience with CI/CD, databases, infra-as-code Comfortable debugging production systems Nice to Have Security/compliance (SOC2, HIPAA) Exposure to AirFlow and MLFlow for scientific workflows MSC/PHD in Machine Learning Biotech / pharma experience Why Helical Live with top pharma High ownership, small team Work at the intersection of AI, biology, and systems Build something that actually changes how medicine is made High ownership, low ego