Computer Vision​/Machine Learning Engineer

Our client, a leading media & entertainment provider, is seeking a Senior Machine Learning Engineer to join its segmentation data science team. You will leverage data, statistical methods, and machine learning to generate model outputs, predictions, and scalable solutions that inform critical decisions and shape the experiences of millions of viewers worldwide. Through model development, analysis, experimentation, and data products, you will build capabilities that are continuously refined through close collaboration with cross-functional stakeholders.

As a Senior Machine Learning contractor on the segmentation data science team, you will develop machine learning solutions for content classification and segmentation. You will work with large-scale content metadata and related data to develop features, train and evaluate classifiers, and build scalable workflows that generate segments for downstream applications. This is a highly hands-on role requiring strong applied machine learning expertise, proficiency in Python and modern data science tools, and the ability to independently take solutions from data exploration and feature development through model evaluation and implementation.

This position is W-2 only. We do not work with third-party firms or C2C arrangements for this role.

Design, develop, evaluate, and implement machine learning classifiers for content classification and segmentation use cases Explore, analyze, and prepare content datasets using Python, pandas, SQL, Spark, and related data science tools Develop features from structured and semi-structured metadata, including categorical, numerical, text-derived, and aggregated features Build robust feature-processing workflows, including missing-value handling, categorical encoding, scaling, normalization, feature selection, and other appropriate transformations Develop multi-class and multi-label classification models using appropriate supervised machine learning techniques, and train, tune, and compare models using cross-validation, and hyperparameter optimization Partner with data scientists, engineers, and content stakeholders to translate requirements into practical machine learning solutions Apply strong software development practices, including modular code, version control, testing, logging, code review, and documentation

Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field, or equivalent practical experience 5+ years of industry experience building and deploying machine learning models in production environments and relevant NLP experience. Strong proficiency in Python, with hands‑on experience using pandas and scikit‑learn for data preparation and machine learning Strong understanding of supervised machine learning and classification techniques, including linear models, decision trees, random forests, ensemble methods, and gradient‑boosted models Strong experience with feature engineering, feature preprocessing, and feature selection for structured and semi-structured datasets Experience developing multi-class and/or multi-label classification models Strong SQL skills and experience querying, joining, aggregating, and analyzing large datasets Ability to independently move from exploratory data analysis and feature development through model training, evaluation, and implementation Strong analytical and problem‑solving skills, with the ability to make pragmatic modeling decisions based on data, project requirements, and delivery constraints Strong written and verbal communication skills, with the ability to clearly explain technical approaches and results to technical and…