Platform Engineer
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Role details
Tech stack
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Job description
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
Requirements
- 3+ years in platform / DevOps / infra
- Strong Kubernetes, Docker, cloud (AWS/GCP/Azure)
- Solid Python
- Experience with CI/CD, databases, infra-as-code
- Comfortable debugging production systems
- High ownership, low ego
Nice to Have
- GPU workloads / ML infra
- Observability tools (Prometheus, Grafana, etc.)
- Security/compliance (SOC2, HIPAA)
- Biotech / pharma experience
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