Senior Machine Learning Engineer - 1665
About The Position
The Senior Machine Learning Engineer will design, develop, and improve machine learning models for content classification and segmentation. The role focuses on building supervised classification models that assign categories, genres, and segments to content, while enhancing existing models and expanding their coverage across content types. The engineer will work across the machine learning lifecycle, including exploratory data analysis, feature engineering, preprocessing, training, tuning, and evaluation. They will process structured and semi-structured datasets using Python, pandas, SQL, and Spark; develop text-based and metadata-driven features; and build scalable workflows for production applications. The role collaborates with data scientists, software engineers, and business stakeholders, and maintains clean, modular, tested, and documented code. This is an 18-month role based in Santa Monica, California, or Seattle, Washington, with an onsite Monday-through-Thursday and remote Friday schedule. The rate is up to $103.50 per hour on W-2. Work authorization is limited to GC, USC, and valid EADs other than OPT, CPT, and H-1B.
Requirements
- At least 5 years of relevant machine learning experience, including substantial hands-on model development and production deployment.
- Strong Python programming skills, including pandas and scikit-learn.
- Hands-on experience with supervised machine learning, particularly classification models.
- Experience with 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.
- 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.
- 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 Haves
- 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.
Responsibilities
- 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 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 machine learning solutions.
- Maintain clean, modular, tested, and documented machine learning code.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Senior
