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Senior Data Scientist

  • California, Glendale

  • 07/02/2026

  • Full Time

  • Active

Job Description:

  • Job Summary
    We are seeking a Sr Data Scientist to design, build, and operationalize production-grade machine learning solutions that support content production, localization, metadata enrichment, intelligent search, and archival workflows across large-scale media systems. The ideal candidate will have strong expertise in applied machine learning, statistical modeling, MLOps, and cloud-native technologies, with the ability to develop scalable AI solutions and collaborate across engineering, operations, and product teams.

    Key Responsibilities
    • Design, develop, train, and optimize machine learning models for media metadata extraction, content classification, entity resolution, semantic search, similarity search, and multimodal understanding.
    • Build predictive and prescriptive models to improve content operations, localization quality, asset matching, retrieval ranking, and automated tagging.
    • Perform feature engineering, statistical analysis, model selection, and model optimization using modern machine learning frameworks.
    • Develop scalable machine learning pipelines using Python, cloud-native services, and enterprise data platforms.
    • Collaborate with Data Engineering teams to design data pipelines for model training, validation, and inference.
    • Build evaluation frameworks and monitoring solutions to ensure model quality, reliability, and drift detection.
    • Containerize, deploy, and maintain machine learning services using CI/CD pipelines and orchestration frameworks.
    • Integrate machine learning models with content production systems, APIs, metadata services, and enterprise platforms.
    • Ensure model reproducibility, versioning, and lifecycle management following enterprise MLOps practices.
    • Apply machine learning techniques to content production, localization, content distribution, archival, retrieval, and semantic search use cases.
    • Partner with product managers, engineering teams, operations teams, and business stakeholders to translate business requirements into AI-driven solutions.
    • Communicate technical concepts, model performance, and implementation trade-offs to technical and non-technical audiences.
    • Evaluate emerging machine learning technologies, vector search solutions, embeddings, and cloud-native AI services to drive continuous innovation.

    Required Qualifications
    • Overall 10+ years of professional experience in Data Science, Machine Learning, Artificial Intelligence, or related technical fields.
    • Strong proficiency in Python, Machine Learning, Statistical Modeling, SQL, and AWS.
    • Experience with Semantic Search, Vector Databases, and Generative AI technologies.
    • Hands-on experience developing, deploying, and operationalizing production-grade machine learning models.
    • Experience implementing scalable MLOps pipelines and machine learning deployment workflows.
    • Strong knowledge of model training, feature engineering, validation, monitoring, and lifecycle management.
    • Experience working with large-scale datasets and distributed computing environments.
    • Strong analytical, problem-solving, and statistical modeling skills.
    • Experience collaborating across engineering, operations, product management, and business teams.
    • Excellent verbal and written communication skills.

    Preferred Qualifications
    • Experience working with media metadata, content intelligence, localization, or multimodal machine learning.
    • Experience with embeddings, vector search technologies, and knowledge graph solutions.
    • Experience with CI/CD, containerization, and orchestration frameworks.
    • Familiarity with cloud-native AI services and enterprise machine learning platforms.

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