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