Warner Bros. Discovery is looking to drive the next wave of data-driven innovation in the Media & Entertainment industry by leveraging data science and applied AI to enhance audience experiences, streamline operations, and unlock business value.
Requirements
- Expertise in designing, building, and deploying production-grade machine learning systems at scale.
- Experience in leading cross-functional teams to deliver end-to-end machine learning solutions, from conceptualization to deployment and optimization.
- Strong expertise in machine learning algorithms, deep learning, reinforcement learning, and statistical modeling techniques.
- In-depth knowledge of data structures, software engineering principles, and system design.
- Experience with distributed computing and cloud technologies (AWS, GCP, Azure) and containerization (Docker, Kubernetes).
- Proficiency in programming languages such as Python, Java, or Scala, and familiarity with ML frameworks like TensorFlow, PyTorch, or Keras.
- Experience working in the Media & Entertainment industry or related sectors, with knowledge of data-driven content recommendations, personalization, and automation.
Responsibilities
- Oversee the end-to-end lifecycle of data science and AI solutions—from problem framing, exploratory analysis, and modeling to deployment, monitoring, and iteration.
- Lead the development and deployment of advanced analytics, machine learning, NLP, computer vision, and generative AI models that address complex business challenges.
- Ensure the creation of robust, scalable, and production-ready AI pipelines, leveraging cloud-native, microservices-based architectures.
- Embed best practices in MLOps, model governance, and responsible AI to ensure reliability, fairness, transparency, and compliance.
- Partner with product management, engineering, and business teams to translate complex business problems into technical Data Science/ AI solutions.
- Collaborate on the integration of ML models into products and workflows, ensuring smooth end-to-end delivery from prototype to production.
- Define and track key performance indicators (KPIs) to measure the success of AI/ ML initiatives and models.
Other
- Bachelor’s degree in Computer Science, Engineering, Data Science, Machine Learning, or a related field from a reputed institution. Master’s degree or PhD preferred.
- 10+ years of experience in the field of machine learning and AI, with at least 8 years in a leadership or managerial role.
- Previous experience leading and scaling ML engineering teams and delivering large-scale ML projects in a fast-paced environment.
- Strong business mindset and ability to solve complex, high-value problems at scale.
- Ability to champion data-driven decision making and thought leadership, elevating the visibility and influence of the AI team across the enterprise.
