MLOps Solutions Engineer (m/f/d)

Overview: Building Bridges Between Code, Customers, and Growth

We’re looking for a high-energy engineer who thrives at the intersection of MLOps technology, customer enablement, and go-to-market execution. ZenML is an open-source MLOps framework, and as adoption grows among enterprises and startups alike, we need someone who can translate technical complexity into clarity — driving successful evaluations, deployments, and long-term customer success.

In this hybrid role, you’ll work across pre-sales engineering, proof-of-concept delivery, customer advocacy, and product strategy. You’ll design demos that wow technical audiences, troubleshoot Kubernetes and tool issues during trials, translate customer insights into roadmap feedback, and help shape how teams use ZenML to run production-grade ML and LLM workflows.

Key Responsibilities (The "Jobs to be Done")

• Pre-Sales & Enablement: Drive technical demos and solution deep-dives with enterprise prospects, tailoring ML and AI workflows and integrations to their environments. Build convincing technical narratives with architecture diagrams and proof-of-value setups. Re-engage leads and qualify promising prospects through community and outbound channels.
• Proof of Concept (PoC): Lead customer trials from setup to success: deploy ZenML via Helm/Terraform, guide pipeline engineering, and troubleshoot any infrastructure or SDK issues. Keep PoCs scoped, on track, and outcome-focused.
• Customer Success & Support: Ensure users extract full value from ZenML by triaging issues, running feature enablement sessions, and engaging new users in community channels. Monitor adoption and proactively address friction points to drive retention.
• Product & Engineering Collaboration: Turn customer learnings into product improvements - from drafting PRDs and testing new features to developing code examples and documentation. Act as a strong advocate for developer experience and seamless deployment.
• Operations, Growth & Evangelism: Optimize GTM systems (billing, CRM, analytics) and share insights across teams. Represent ZenML at events, deliver talks, and co-create content that spreads best practices and user success stories.

Tech You'll Work With

• The Tool: ZenML (You will become a power user/expert).
• The Infrastructure: Kubernetes (deploying and debugging apps), Docker, Helm, Terraform.
• The Code: Python (Scripting, SDK, contributing to codebase), Go (optional, Terraform provider)
• The Clouds: AWS (EKS), GCP (GKE), Azure (AKS).

What We're Looking For

• Full-Stack MLOps Thinker: You understand both the ML lifecycle and the infrastructure it runs on.
• Customer Engineer Mindset: You can talk to data scientists, DevOps engineers, and decision-makers with equal confidence.
• Strong Communicator: You enjoy teaching, writing, and simplifying complex technical concepts.
• Builder Mentality: You don’t just identify friction — you script, automate, or prototype the fix.