Machine Learning Engineer III – Job Description
Summary
The Machine Learning Engineer is responsible for designing, developing, and optimizing machine learning models and systems. The role involves working with data science prototypes, selecting suitable algorithms, and ensuring high-quality model performance through testing and retraining.
Responsibilities
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Study and transform data science prototypes into production-ready solutions.
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Design end-to-end machine learning systems.
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Research, evaluate, and implement suitable ML algorithms and tools.
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Develop ML applications based on business and technical requirements.
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Select appropriate datasets and data representation methods.
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Run machine learning tests and experiments to validate model performance.
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Perform statistical analysis and fine-tuning based on test results.
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Train and retrain models as needed to ensure accuracy and relevance.
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Extend or enhance existing ML libraries and frameworks.
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Stay updated on advancements and trends in machine learning and AI.
Requirements
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Experience as a Machine Learning Engineer or in a similar role.
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Strong understanding of data structures, data modeling, and software architecture.
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Deep knowledge of mathematics, probability, statistics, and algorithms.
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Ability to write high-quality, robust code in Python, Java, and R.
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Familiarity with ML frameworks such as Keras or PyTorch, and libraries such as scikit-learn.
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Excellent communication skills and ability to collaborate effectively.
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Strong analytical and problem-solving capabilities.
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Bachelor’s degree in Computer Science, Mathematics, or a related field (Master’s preferred).