Platform Engineer

Helical; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Job summary

Helical is building an AI-native biology lab and production-ready AI-driven workflows. We seek a Platform Engineer to scale the infrastructure behind our virtual AI lab, debugging Kubernetes and refining architecture while shipping to production.

You will own cloud infra, ML training and inference pipelines, and CI/CD across multi-tenant environments. The role involves collaboration with ML, backend, and product teams to enable scalable, secure, and observable systems for AI-driven drug

Qualifications

• 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.

Responsibilities

• 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.

Skills

Kubernetes

Docker

Cloud platforms

ML infra

Multi-tenant architectures

Autoscaling

CI/CD

Infra-as-code

Production debugging

Python/Bash

Tools

Kubernetes

Job 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