Senior Machine Learning Engineer

Warner Bros. Discovery-posted 2 days ago
Full-time • Mid Level
San Francisco, CA
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We are seeking a Staff Machine Learning Engineer to lead the development and deployment of scalable machine learning solutions for the Audience Intelligence team. You will work on projects such as building scalable lookalike and predictive audiences, user behavior modeling, ML forecasting systems, ML-based ID resolutions, and developing ML solutions to better understand HBO Max user bases. This role blends deep technical expertise, research rigor, and production-grade engineering practices. You will mentor junior engineers and scientists, collaborate cross-functionally, and advance our ML capabilities through innovation and thought leadership.

  • Model Development: Design and implement machine learning models for audience intelligence applications, including lookalike and predictive audience generation, user behavior modeling, ML forecasting, ML-based ID resolution, and ML-based user base characterization for HBO Max. Stay current with ML research, explore new methodologies, and contribute to the company’s research agenda through publications and open-source contributions when possible.
  • End-to-End Model Delivery: Architect, build, and maintain complete ML pipelines from data ingestion and processing to model deployment and monitoring in production environments, ensuring robust delivery and operational excellence.
  • Infrastructure & Automation: Develop robust, scalable infrastructure and automated workflows for ML training, evaluation, and deployment, using best practices in MLOps.
  • Cross-Functional Collaboration: Work closely with product, engineering, and business stakeholders to translate requirements into effective ML solutions.
  • Mentorship: Guide and mentor junior engineers and scientists, fostering a culture of knowledge sharing and technical excellence.
  • Production Operations: Ensure robust model deployment, monitoring, and optimization to meet business requirements for latency, concurrency, and reliability.
  • MLOps Governance & Compliance: Promote best practices around MLOps among broader data science groups to ensure consistent model quality and faster deployment cycles. Ensure end-to-end governance and compliance for ML systems by enabling model traceability (e.g., audit trails for model changes), enforcing data privacy standards and meeting regulatory requirements relevant to our industry.
  • Education: PhD or MSc in Machine Learning, Computer Science, Data Science, or a closely related field.
  • Experience: 3+ years (PhD) or 5+ years (MSc) of hands-on experience in machine learning engineering, including model development and production deployment.
  • Technical Skills:
  • Proficient in Python and ML frameworks such as PyTorch, TensorFlow, MLflow, and SageMaker.
  • Expert on SQL and large-scale data processing languages.
  • Proven track record of deploying ML models to production.
  • Familiarity with distributed computing systems (Spark, EMR).
  • Experience with cloud platforms (AWS, Databricks, Snowflake).
  • Strong computer science fundamentals, including data structures, algorithms, and system design.
  • Mindset: Strong desire to learn new techniques and adapt to evolving business needs.
  • Communication: Ability to clearly articulate ML concepts to diverse stakeholders.
  • Experience in AI/ML advertising solutions, marketing sciences, recommendations, search, ranking and personalization systems.
  • Publications in top tier ML conferences or contributions to open-source projects.
  • Experience with CI/CD, DevOps, and MLOps principles for building and deploying ML systems.
  • health insurance coverage
  • an employee wellness program
  • life and disability insurance
  • a retirement savings plan
  • paid holidays and sick time and vacation
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