Senior Software Engineer, Machine Learning - Ad Platforms

$138,900 - $186,200/Yr

Disney Entertainment & ESPN Technology - Santa Monica, CA

Full-time - Mid Level

Santa Monica, CA

About the position

The Sr Software Engineer position at Disney Entertainment & ESPN Technology focuses on building and enhancing the machine learning platform for advertising decisioning. This role is crucial for developing state-of-the-art AI solutions to optimize advertising performance across Disney's platforms, including Hulu and ESPN+. The engineer will work within a cross-domain team to deliver end-to-end solutions that leverage machine learning and big data processing, contributing to the overall success of Disney's advertising initiatives.

Responsibilities

• Build next-gen machine learning platform for advertising decisioning to fit evolving business needs
• Develop scalable and efficient approaches for large scale data analysis
• Collaborate with researchers to productize cutting edge innovations
• Design scalable distributed systems with performance, scalability, reusability and flexibility
• Advocate the best engineering practices, including the use of design patterns, CI/CD, code review and automated testing
• Contribute to all aspects of the software lifecycle: design, experimentation, implementation and testing
• Collaborate with program managers, product managers, SDET, and researchers in an open and innovative environment

Requirements

• Bachelor's degree in computer science or related field of study
• 5+ years of professional programming and design experience in Java, Python, Scala, etc.
• Knowledge of AI/ML technologies and typical technical stacks
• Experience building industry-level high availability and scalable microservices
• Knowledge of system, application design and architecture
• Knowledge of big data processing and big data technologies
• Passionate about understanding the ad business and seeking innovation opportunities to enhance business effectiveness
• Passionate about technology, and open to interdisciplinary collaborations

Nice-to-haves

• Domain knowledge about advertising
• Experience with machine learning platforms like TensorFlow, Kubeflow, PyTorch, Databricks, AWS SageMaker, etc.
• Experience with GenAI technologies and LLMs
• Experience with feature store, audience segmentation and MLOps

Benefits

• Medical insurance
• Financial benefits
• Bonus and/or long-term incentive units may be provided as part of the compensation package