Machine Learning Platform Engineer Mock Interview

Service Description:

ML Platform Engineering is one of the most in-demand and least well-understood roles in the industry — sitting at the intersection of data engineering, MLOps, and infrastructure. This mock interview is led by a Senior Engineering Manager who architected and scaled end-to-end ML platforms in production at Talabat (DeliveryHero) and HelloFresh, covering training, deployment, and model serving across GCP and AWS.

What to expect:

• 🎯 40-minute mock interview covering ML platform architecture, MLOps, model training pipelines, model serving, feature stores, and infrastructure (Kubernetes, GKE, EKS)
• 💬 20-minute feedback session and open discussion on your performance, gaps, and how to sharpen your answers
• 🧠 Real interview perspective from someone who has built ML platforms on Vertex AI, BentoML, MLflow, Kubeflow, and Airflow in production
• 📋 Please share your resume before the session so the interview is tailored to your background and target role

Topics that may be covered:

• ML pipeline design and orchestration
• Model serving, versioning, and monitoring
• Feature engineering and feature stores
• Infrastructure for ML — Kubernetes, GKE, EKS
• MLOps best practices and tooling
• Cost optimisation for ML workloads