Proteins are the molecular machines of life, used for many therapeutic, diagnostic, chemical, agricultural and food applications. Designing and optimizing proteins currently takes a lot of expert knowledge and manual effort, through the use of custom computational and biological tools. However over the past few years, machine learning has completely changed this story: we can now build high-fidelity models of proteins in computers.
At Cradle, we build these models. We offer a software platform for AI-guided lead optimization of proteins, so that biologists can design proteins faster and at scale. We’re already used by clients across pharma, biotech, agritech, foodtech, and academia.
We're an experienced team, now of just over 40 people. We've built many successful products before and have enough funding for multiple years of runway. Our technical roles are split between machine learning, our web platform, infrastructure & scaling, and wet lab.
We're focused on building the best possible team culture. We're distributed across two locations, and are flexible about when and where we work.
We offer our employees a top of the market salary, a generous equity stake in the company and a wide range of benefits from health and wellbeing, financial, to training and career progression opportunities.
We’re looking to add a full-time DevOps/Cloud expert with an interest in security to our team.
Together with our existing DevOps engineer and the rest of the engineering team, you will build and maintain our GitOps cloud infrastructure, perform troubleshooting tasks and help the engineering team with their decisions regarding our infrastructure setup. You will also act as a go-to person to consult engineers on best practices regarding CI/CD, security, observability and operations.
You will not shy away from jumping into an ML/Ops Python codebase and help the ML team with their orchestration workflows.
Responsibilities:
As a DevOps engineer, you will be responsible for:
Improving CI/CD automation of our Kubernetes based deployments using Terraform and ArgoCD
Improving Cradle’s multi-tenant Terraform configuration and harden our Kubernetes cluster - setting up RBAC and access policies, configuring pod security standards
Help unify monitoring and alerting for our production deployment and infrastructure
Setting up a security information and events management system to collect logs and monitor events from production and corporate networks
Help the ML Ops team improve workflow orchestration
3+ years of industry experience in setting up, maintaining and troubleshooting Kubernetes systems
Native Terraform speaker
Excellent coding skills, preferably in Python
Solid understanding of networking in cloud environments
Familiarity with GCP (specifically IAM, GKE, GCE, GCS)
Experience in database administration (preferably PostgreSQL)
Interest in IT security and SecOps
Experience in ML-ops or infrastructure for data processing pipelines
Did we pique your interest? We'd love to hear from you. Please use this form to apply directly.