City: Santa Monica, CA & Seattle, WA
Onsite / Hybrid / Remote: Hybrid. Onsite Monday through Thursday. Remote Friday.
Duration: 18 months
Rate Range: Up to $103.50/hr on w2
Work Authorization: GC, USC, All valid EADs except OPT, CPT, H1B
Must Have:
- 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.
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 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.
Qualifications:
- 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.