Professional Machine Learning Engineer

Framing ML problems and building solutions. Automating and orchestrating ML pipelines. Monitoring, optimizing, and maintaining models.

📝 240 Questions⏱️ 120 min🎯 Pass: 70%

👤 Who Is This For?

  • ML engineers deploying models on Vertex AI
  • Data scientists building production ML pipelines
  • AI practitioners automating model retraining

📊 Exam Domains

🎯Framing ML Problems15%
🏗️Architecting ML Solutions18%
📊Data Preparation & Processing20%
🧠ML Model Development25%
⚙️ML Pipeline Automation & Orchestration22%

Practice by Topic

BigQuery10 Questions
Cloud Armor10 Questions
Cloud Build10 Questions
Cloud CDN10 Questions
Cloud Deployment Manager10 Questions
Cloud Firestore10 Questions
Cloud HTTP(S) Load Balancing10 Questions
Cloud IAM10 Questions
Cloud Key Management Service10 Questions
Cloud Network Load Balancing10 Questions
Cloud SQL10 Questions
Dialogflow10 Questions
Document AI10 Questions
Google Cloud Armor10 Questions
Google Cloud Functions10 Questions
Google Cloud Observability10 Questions
Google Cloud Storage10 Questions
Google Compute Engine10 Questions
Persistent Disk10 Questions
Scenario Based20 Questions
Vertex AI10 Questions
Virtual Private Cloud (VPC)10 Questions
VPC Firewall Rules10 Questions