LR074 Machine Learning Engineer II

Machine Learning Engineer II, Cloud Computing Technologies Agile Development Labor Rate makes use of huge amount of data and skills to interpret and analyze the data sets for machine learning model development. Design machine learning programs, Train and retrain machine learning systems. Work on frameworks. Undertaking machine learning experiments and test Fine tuning test results. Developing deep learning systems to various use cases based on the company needs, implement suitable Artificial Intelligence/Machine Learning algorithms. Perform statistical analysis, analyzing the Machine learning Algorithms that could be used to solve a given problem. Troubleshooting and verifying data quality, and ensuring data quality via cleaning. 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 Statistical analysis and Fine-Tune the Testing Results. Select the Right Training Data Sets for Machine learning Model Development. Perform the Training models and tuning their hyperparameters. Choose and Implement the Right Machine Learning Algorithm. Select and Implement Right Machine Learning Algorithms. Understand Business Objectives and Developing the ML Models. Perform statistical analysis. Undertake machine learning experiments and tests and fine-tuning test results. Train and retrain systems. Work on frameworks. Help shape the direction of Machine Learning and Artificial Intelligence. Design and implement new features and perform code reviews. Machine Learning Engineer II requires at least a bachelor degree in computer science, computer engineering, mathematics or any other related field with 6+ years of experience working as a Machine learning engineer or related specialty. Core skills required includes; Ability to write code in Java and Python. Knowledge on basics of math and probability. Good understanding and strong knowledge in algorithms and statistics. Appreciation of data modelling, software architecture and data structures. Past experience of working in frameworks in last position.

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