- Miguel Miró-Granada Martín-AsínThis acknowledges thathas successfully completed all the requirements to be recognized as aGoogle Cloud CertifiedProfessional Machine Learning EngineerSeries ID: 2499 Issue Date: 23 Sep 2022 Expiration Date: 23 Sep 2024 ID: 6c0bb25ef18d4e95bf0248b1be6f25ee Certified As: Miguel Miro-GranadaThomas KurianCEO, Google Cloud

Miguel Miró-Granada Martín-Asín
This acknowledges that
has successfully completed all the requirements to be recognized as a
Google Cloud Certified
Professional Machine Learning Engineer

Series ID: 2499
Issue Date: 23 Sep 2022
Expiration Date: 23 Sep 2024
ID: 6c0bb25ef18d4e95bf0248b1be6f25ee
Certified As: Miguel Miro-Granada
Thomas Kurian
CEO, Google Cloud


Miguel Miro-Granada
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.
The Professional Machine Learning Engineer exam assesses your ability to:
• Architect low-code ML solutions
• Collaborate within and across teams to manage data and models
• Scale prototypes into ML models
• Serve and scale models
• Automate and orchestrate ML pipelines
• Monitor ML solutions
Skills / Knowledge
- Machine Learning
- Google Cloud Platform
Issued on
September 23, 2022
Expired on
September 23, 2024