A Professional Machine Learning Engineer builds, evaluates, productionizes, and optimizes ML models by using Google Cloud technologies and knowledge of proven models and techniques. The ML Engineer handles large, complex datasets and creates repeatable, reusable code. The ML Engineer considers responsible AI and fairness throughout the ML model development process, and collaborates closely with other job roles to ensure long-term success of ML-based applications. The ML Engineer has strong programming skills and experience with data platforms and distributed data processing tools. The ML Engineer is proficient in the areas of model architecture, data and ML pipeline creation, and metrics interpretation. The ML Engineer is familiar with foundational concepts of MLOps, application development, infrastructure management, data engineering, and data governance. The ML Engineer makes ML accessible and enables teams across the organization. By training, retraining, deploying, scheduling, monitoring, and improving models, the ML Engineer designs and creates scalable, performant solutions.
*Note: The exam does not directly assess coding skill. If you have a minimum proficiency in Python and Cloud SQL, you should be able to interpret any questions with code snippets.
The Professional Machine Learning Engineer exam assesses your ability to:
- Architect low-code ML solutions
- Scale prototypes into ML models
- Automate and orchestrate ML pipelines
- Collaborate within and across teams to manage data and models
- Serve and scale models
- Monitor ML solutions
Before attempting the Machine Learning Engineer exam, it's recommended that you have 3+ years of industry experience, including 1 or more years designing and managing solutions using Google Cloud.
Exams and recommended training
- Google Cloud Fundamentals: Big Data and Machine Learning (GCF-BDM)
- Advanced Machine Learning with TensorFlow on Google Cloud Platform (MLTF)
About this certification exam:
- Length: Two hours
- Language: English
- Exam format: Multiple choice and multiple select
- Exam Delivery Method:
- Take the online-proctored exam from a remote location, review the online testing requirements.
- Take the onsite-proctored exam at a testing center, locate a test center near you.
- Prerequisites: None
- 3+ years of industry experience including 1 or more years designing and managing solutions using Google Cloud.