Manager, Machine Learning Engineering - Warner Bros. Discovery

Key Responsibilities

• Architect and develop end‑to‑end ML pipelines for large‑scale content recommendation and personalization.
• Collaborate with data scientists, product managers, and software engineers to translate business problems into ML solutions.
• Implement MLOps practices: model versioning, CI/CD, monitoring, and automated retraining on AWS.
• Optimize model performance and inference latency using GPU/TPU resources and distributed training.
• Mentor junior engineers and promote best practices in code quality, testing, and documentation.

Requirements

• 5+ years of experience in production ML engineering.
• Proficiency in Python, TensorFlow or PyTorch, and experience with AWS services (SageMaker, ECS, Lambda).
• Strong background in data engineering, SQL, and big‑data processing (Spark, Hadoop).
• Hands‑on experience with MLOps tools (MLflow, Kubeflow, Airflow).
• Excellent communication skills and a collaborative mindset.