Senior Machine Learning Engineer - 1665

• Design, develop, and improve machine learning models for content classification and segmentation.
• Build classification models that automatically assign content categories, genres, and segments.
• Enhance existing machine learning models and expand classification coverage across different content types.
• Develop multi-class and multi-label classification models using supervised learning techniques.
• Perform exploratory data analysis, feature engineering, model training, tuning, and evaluation.
• Process structured and semi-structured datasets using Python, pandas, SQL, and Spark.
• Develop text-based and metadata-driven features to improve classification accuracy.
• Apply techniques such as categorical encoding, normalization, feature selection, and hyperparameter optimization.
• Build scalable machine learning workflows to support production applications.
• Collaborate with data scientists, software engineers, and business stakeholders to implement ML solutions.
• Maintain clean, modular, tested, and documented machine learning code.

• 5+ years of hands-on industry experience developing and deploying machine learning models in production.
• Strong Python programming skills, including pandas and scikit-learn.
• Hands-on experience with supervised machine learning, particularly classification models.
• Experience with Natural Language Processing (NLP), including text-based feature development.
• Strong experience with feature engineering, preprocessing, and model evaluation.
• Strong SQL skills for querying and analyzing large datasets., * Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field, or equivalent practical experience.
• Minimum 5 years of relevant machine learning experience, with substantial hands-on model development.
• Strong understanding of classification algorithms, including logistic regression, decision trees, random forests, ensemble methods, and gradient-boosted models.
• Experience building, training, evaluating, and deploying machine learning classifiers.
• Experience with multi-class and/or multi-label classification.
• Experience with NLP techniques and text-derived features.
• Strong knowledge of cross-validation, model performance metrics, and hyperparameter tuning.
• Ability to independently deliver machine learning solutions from initial data exploration through production implementation.
• Experience with software development practices, including Git, testing, logging, and code reviews.

Nice to Have

• Master’s degree in Computer Science, Machine Learning, Statistics, Mathematics, or a related field.
• Experience in media, entertainment, streaming, or digital content platforms.
• Experience building classifiers using content metadata, catalog data, or high-dimensional datasets.
• Experience with NLP techniques such as TF-IDF, text embeddings, and semantic representations.
• Experience with workflow orchestration tools such as Airflow or Luigi.
• Experience with AWS or similar cloud environments.
• Experience with search, recommendation systems, or content categorization.