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.

Training Available:

Online Self-Paced Training: Candidates will be provided with comprehensive course materials and guides, allowing them the flexibility to study at their own pace.

Instructor-Led Training: Experience expert guidance from certified trainers, delivered either online or at our institute. Course duration details can be found below the “Know More” button.

Exam:

You have the flexibility to take the exam from the comfort of your home, remotely, or if you are in Bangalore, you are welcome to visit our office for the exam.

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