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