Director, ML Engineering & Infrastructure
The Machine Learning team at Tubi drives the innovation behind personalized user experiences. With the largest inventory in the industry and hundreds of millions of viewers, we tackle problems in the space of recommendations, search, content understanding, and ads optimization that shape the future of streaming.
We are seeking a Director of Machine Learning Engineering and Infrastructure to lead a hybrid team bridging advanced ML engineering with world-class infrastructure design. In this role, you will own the strategic direction and execution for scaling our machine learning capabilities while ensuring our distributed systems and infrastructure can support innovation at massive scale. You will combine technical depth with leadership excellence to guide teams that deliver both foundational ML systems and high-performance distributed services.
Key responsibilities include leading and managing high-performing teams across ML engineering and ML infrastructure, fostering a culture of innovation, collaboration, and growth. You will define and execute the strategic roadmap for ML systems, including recommendation, personalization, and ads optimization. Overseeing the design, development, and deployment of scalable ML pipelines—data ingestion, feature engineering, model training, evaluation, and serving—is essential. Additionally, you will architect distributed systems to support ML workloads at scale, ensuring reliability, observability, and operational excellence. Collaboration with Product, Engineering, and Content teams to align on business goals and deliver impactful ML-driven experiences is also a key aspect of the role.
The ideal candidate will have over 10 years of industry experience spanning machine learning engineering and distributed systems, with at least 3 years in leadership and management roles, demonstrating the ability to build and lead strong technical teams. An MSc or Ph.D. in Computer Science, Machine Learning, or a related field, or equivalent practical experience, is required. Proven expertise in building and deploying end-to-end ML systems at scale, including recommendation and personalization systems, is essential. A strong background in distributed systems architecture, including low-latency services, streaming platforms, and large-scale serving, is necessary. Hands-on experience with deep learning frameworks (e.g., TensorFlow, PyTorch) and ML infrastructure technologies is also required. A track record of delivering high-quality, scalable, and fault-tolerant systems, along with excellent communication skills and the ability to influence product and technical strategy, is crucial. Proven experience deploying large-scale serving systems on AWS and demonstrated expertise in leveraging Databricks for large-scale data processing and ML workflows is also expected.
The compensation for this role in high-cost labor markets such as Los Angeles, New York City, and San Francisco ranges from $292,000 to $417,200 USD annually, depending on education, skills, experience, and location. This role is also eligible for an annual discretionary bonus, long-term incentive plan, and various benefits including medical, dental, and vision insurance, a 401(k) plan, paid time off, and other benefits in accordance with applicable plan documents.
Tubi offers a dynamic and innovative work environment, fostering a culture of collaboration and growth. As a division of Fox Corporation, Tubi provides employees with the opportunity to work on cutting-edge projects in the streaming industry, contributing to the future of entertainment.