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Machine Learning Engineer

A Machine Learning Engineer is responsible for contributing to data-driven analysis and development of intelligent systems. This role involves working across key areas such as Deep Learning Frameworks (TensorFlow, PyTorch), Model Deployment & Selling (MLOps), while applying technical knowledge in machine learning, big data (spark/hadoop), statistical modeling, deep learning, data mining.

Machine Learning Engineer

What they do

As a key professional in the Data Science & Artificial Intelligence industry, the Machine Learning Engineer plays a vital part in the sector's mission: data-driven analysis and development of intelligent systems. Specifically, they focus on overseeing or executing specialized tasks that ensure efficient operations, high-quality outcomes, and adherence to industry standards. Their work directly supports the organization's goals and implementation of best practices.

Specialties

Deep Learning Frameworks (TensorFlow, PyTorch)

Model Deployment & Selling (MLOps)

NLP & Computer Vision

Algorithm Optimization

Feature Engineering

Machine Learning Engineer specialties

Pathways
(education / training)

Bachelor's Degree In Engineering Or A Related Technical Field. Professional Licensure (e.g., PE) May Be Required Or Beneficial. Experience With CAD Software And Simulation Tools Is Often Essential.

Connection to the SDGs

Industry, Innovation and Infrastructure

Skills