Staff Product Software Engineer (ML)
Company: Disneycareers
Location: Bangalore, India
Type: Full-time
Posted: 2026-08-26
About this role
Job Posting Title:
Staff Product Software Engineer (ML)
Req ID:
10152210
Job Description:
Ad Platforms organization within Disney Entertainment and ESPN Technology is fully responsible for building, enhancing and maintaining the high-performance, distributed, microservice-based Advertising Platform across all of Disney online properties, including Hulu and ESPN+. We build and maintain proprietary technology, ranging from ad serving and ad delivery, campaign management, reporting as well as all the integrations internal and external that come with evolving and maintaining a best-in-class video advertising business.
Our mission is to advance AI and machine learning capabilities across Ad Platform by delivering scalable, high impact AI/ML and data science solutions that enhance Ad serving capabilities. We are seeking a seasoned Lead Machine Learning Engineer to join this innovative team to spearhead initiatives that shape the future of advertising technology.
Job Summary:
We are looking for a proactive and innovative Lead Machine Learning Engineer to join our team. This pivotal role involves leading the development of prediction and/or optimization engines for our addressable ad platforms. The ideal candidate will have significant experience in designing and implementing machine learning technologies and/or data-driven algorithms, making this an excellent opportunity.
This role offers a unique leadership opportunity for someone who thrives at the intersection of technical excellence, strategic impact, and cross-functional collaboration.
Responsibilities and Duties of the Role:
● Drive ground-breaking innovation and apply state of the art AI and machine learning in a variety of areas to enhance every aspect of advertising.
● Invent and iterate novel solutions for complex ad challenges with fast turnaround.
● Lead the ad algorithm architecture design and iteration of the advertising system.
● Develop scalable and efficient approaches for large scale...