Senior Machine Learning Engineer - 1665

Santa Monica, CA, US • Posted 1 day ago • Updated 3 hours ago
Full Time
On-site
USD 103.50 per hour
Fitment

Dice Job Match Score™

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Job Details

Skills

  • Employment Authorization
  • scikit-learn
  • Management
  • Supervised Learning
  • Data Analysis
  • Evaluation
  • Python
  • Pandas
  • SQL
  • Apache Spark
  • Normalization
  • Optimization
  • Collaboration
  • Data Science
  • Algorithms
  • Logistic Regression
  • Decision Trees
  • Ensemble
  • Training
  • Performance Metrics
  • Software Development
  • Git
  • Testing
  • Computer Science
  • Machine Learning (ML)
  • Statistics
  • Mathematics
  • Media
  • Streaming
  • Meta-data Management
  • Natural Language Processing
  • tf-idf
  • Semantics
  • Workflow
  • Orchestration
  • Amazon Web Services
  • Cloud Computing

Summary

Job Description
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: 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.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: RTX1d3dc7
  • Position Id: 9452297beca519d26dca5394ef1ab6d3
  • Posted 1 day ago
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