Machine learning engineer do one of the toughest job to create a ML or AI-based model that can work properly with best performance. Practically a machine learning engineer’s job is close to data scientist, as both need huge amount of data and skills to interpret and analyze the data sets for model development.
What Does A Machine Learning Engineer Do?
Machine learning engineers have to carryout the the process of organizing the process of developing the such models. They ensure the training data required for machine learning services and algorithm, these professionals acquire the labeled data.
These professionals also choose the right algorithms as per the model compatibility and requirement. And they are also responsible to feed data into models that is defined by the data scientists. Moreover, they also take theoretical data science models and help scale them to level of model production for final prediction.
Apart from that, ML engineers also build the programs that can control machines. And the algorithm developed by machine learning engineers enable a machines to recognize the patterns in its own programming data and teach itself to understand commands and even think for itself for final prediction in real-life.
Role & Duties of Machine Learning Engineers:
- Research, Design and Frame Machine Learning Systems
- Understand and Transform the Prototypes of Data Science
- Verifying data quality, and/or ensuring it via data cleaning
- Perform Machine Learning Model Tests and Experiments
- Develop the Machine Learning Model as per the Needs
- Perform the Training models and tuning their hyperparameters
- Perform Statistical analysis and Fine-Tune the Testing Results
- Choose and Implement the Right Machine Learning Algorithm
- Select and Implement Right Machine Learning Algorithms
- Understand Business Objectives and Developing the Ml Models
- Select the Right Training Data Sets for ML Model Development
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