The Platform Engineer will build and scale the infrastructure for AI-driven drug discovery, focusing on Kubernetes management, cloud infrastructure, and automation using Python and Bash.
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
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