PMLE: Professional Machine Learning Engineer

Description

A Professional Machine Learning Engineer designs, builds, and productionizes ML models to solve business challenges using Google Cloud technologies and knowledge of proven ML models and techniques. The ML Engineer considers responsible AI throughout the ML development process, and collaborates closely with other job roles to ensure long-term success of models. The ML Engineer should be proficient in all aspects of model architecture, data pipeline interaction, and metrics interpretation. The ML Engineer needs familiarity with foundational concepts of application development, infrastructure management, data engineering, and data governance. Through an understanding of training, retraining, deploying, scheduling, monitoring, and improving models, the ML Engineer designs and creates scalable solutions for optimal performance.

Adaptive Test Technology
We use our proprietory "Adaptive Test Tech (TM)" which adapts the questioning sequence & complex, based on the sucess of the questions attempted.

No. of Questions
60
Exam Duration
60 mins
Questions Pool
120

Skills Measured
Domain
Frame ML problems
Architect ML solutions
Design data preparation and processing systems
Develop ML models
Automate & orchestrate ML pipelines
Monitor, optimize, and maintain ML solutions

PMLE Certification Related Links

PMLE Certification Link PMLE Certification Poster