Senior Platform Engineer – Customer Facing

Senior Platform Engineer – Customer Facing

Overview: Architect the Infrastructure of MLOps

We are looking for a heavy-hitting infrastructure engineer who lives in Kubernetes but understands the reality of enterprise deployments. ZenML is an open-source MLOps framework, and as we scale our ZenML Cloud and Enterprise offerings, we need someone to own the “plumbing” that makes ML pipelines run anywhere.

This is a unique hybrid role. You won’t just be maintaining internal clusters; you will be building core product features (like our new workload manager and scheduler) AND helping our most advanced customers architect their MLOps stacks.

Key Responsibilities

• Build “Infra-Heavy” Product Features: You will design and implement core features in ZenML Pro, such as native schedulers and the workload manager that triggers pipelines across hybrid clouds.
• Own the ZenML Pro (SaaS) Infrastructure: ensuring our managed control plane is resilient, scalable, and secure using modern SRE practices (Grafana, Prometheus, Alerting).
• Enterprise Architecture & PoCs: You will be the “Special Forces” engineer we send in when a major enterprise customer needs to deploy ZenML on a complex, air-gapped, or custom Kubernetes setup. You will unblock them and feed those learnings back into the product.
• Developer Experience: Abstracting the complexity of K8s away from the Data Scientists who use our tool.

Tech You’ll Work With

• The Core: Kubernetes (Deep knowledge required – CKA level), Docker, Terraform, Helm.
• The Code: Python (for ZenML) and likely Go (for controllers/operators).
• The Clouds: AWS (EKS), GCP (GKE), Azure (AKS).
• The Stack: PostgreSQL, SQLModel, FastAPI.

What We’re Looking For

• The K8s Native: You don’t just use Kubernetes; you understand its internals. You’ve written Helm charts from scratch, debugged failed ingress controllers, and wrestled with VPC peering.
• Infrastructure as Code (IaC) Master: You hate clicking buttons in the AWS console. If it isn’t in Terraform, it doesn’t exist.
• Code + Ops: You are not just a SysAdmin. You can write production-quality code (Python or Go) to build features, not just scripts.
• Customer Empathy: You are comfortable jumping on a call with a customer’s DevOps team to debug a deployment. You can explain complex infra concepts to Data Scientists without overwhelming them.
• Problem Solver: You enjoy the detective work of figuring out why a pod is crashing in a customer’s obscure private cloud environment.

Why This Role Matters

• High Impact: You will be the bridge between our code and the real world. You will build the engine that executes ML pipelines for thousands of users.
• Technical Breadth: You will see every type of cloud architecture imaginable. You will become a master of “running things anywhere.”
• Open Source: You will be contributing to a major open-source project and building your reputation in the MLOps community.