Director, ML Engineering & Infrastructure
at Tubi
- Seniority
- Director Plus
- Work model
- Hybrid
- Location
- San Francisco, CA; Los Angeles, CA; New York, NY (Hybrid); USA - Remote
- Posted
- 18d ago
awsdatabrickstensorflowpytorch
at Tubi
<h4><strong>About the Role:</strong></h4> <p>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.</p> <p>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.</p> <p><strong>What You'll Do: </strong></p> <ul> <li>Lead and manage high-performing teams across ML engineering and ML infrastructure, fostering a culture of innovation, collaboration, and growth.</li> <li>Define and execute the strategic roadmap for ML systems, including recommendation, personalization, and ads optimization.</li> <li>Oversee the design, development, and deployment of scalable ML pipelines: data ingestion, feature engineering, model training, evaluation, and serving.</li> <li>Architect distributed systems to support ML workloads at scale, ensuring reliability, observability, and operational excellence.</li> <li>Partner closely with Product, Engineering, and Content teams to align on business goals and deliver impactful ML-driven experiences.</li> <li>Support best practices in experimentation, evaluation, and ML system monitoring.</li> <li>Ensure cost efficiency, scalability, and performance in ML infrastructure investments.</li> </ul> <p><strong>Your Background:</strong></p> <ul> <li>10+ years of industry experience spanning machine learning engineering and distributed systems.</li> <li>3+ years of leadership and management experience, with a proven ability to build and lead strong technical teams.</li> <li>MSc or Ph.D. in Computer Science, Machine Learning, or related field, or equivalent practical experience.</li> <li>Proven expertise in building and deploying end-to-end ML systems at scale, including recommendation and personalization systems.</li> <li>Strong background in distributed systems architecture, including low-latency services, streaming platforms, and large-scale serving.</li> <li>Hands-on experience with deep learning frameworks (e.g., TensorFlow, PyTorch) and ML infrastructure technologies.</li> <li>Track record of delivering high-quality, scalable, and fault-tolerant systems.</li> <li>Excellent communication skills and ability to influence product and technical strategy.</li> <li>Proven experience deploying large-scale serving systems on AWS and demonstrated expertise in leveraging Databricks for large-scale data processing and ML workflows</li> </ul> <p> </p><div class="content-pay-transparency"><div class="pay-input"><div class="description"><p style="font-weight: 400;">Pursuant to state and local pay disclosure requirements, the pay range for this role, with final offer amount dependent on education, skills, experience, and location is listed annually below. This role is also eligible for an annual discretionary bonus, long-term incentive plan, and various benefits including medical/dental/vision, insurance, a 401(k) plan, paid time off and other benefits in accordance with applicable plan documents.</p></div><div class="title">High cost labor markets such as but not limited to Los Angeles, New York City, and San Francisco</div><div class="pay-range"><span>$292,000</span><span class="divider">—</span><span>$417,200 USD</span></div></div></div><div class="content-conclusion"><hr> <p style="font-weight: 400;">Tubi is a division of Fox Corporation, and the FOX Employee Benefits summarized <a href="https://drive.google.com/file/d/1I_N5Kz_AWxSaiTvS-jr1gqzKLXM3krY3/view?usp=sharing" target="_blank">here</a>, covers the majority of all US employee benefits. The following distinctions below outline the differences between the Tubi and FOX benefits:</p> <ul style="font-weight: 400;"> <li>For US-based non-exempt Tubi employees, the FOX Employee Benefits summary accurately captures the Vacation and Sick Time.</li> <li>For all salaried/exempt employees, in lieu of the FOX Vacation policy, Tubi offers a Flexible Time off Policy to manage all personal matters.</li> <li>For all full-time, regular employees, in lieu of FOX Paid Parental Leave, Tubi offers a generous Parental Leave Program, which allows parents twelve (12) weeks of paid bonding leave within the first year of birth, adoption, surrogacy, or foster placement of a child in addition to applicable government leave program(s) and FOX’s short-term disability policy. This time is 100% paid through a combination of any applicable state, city, and federal leaves and wage-replacement programs in addition to contributions made by Tubi.</li> <li>For all full-time, regular employees, Tubi offers a monthly wellness reimbursement.</li> </ul> <h4>About Tubi:</h4> <p>Boldly built for every fandom, Tubi is a free streaming service that entertains over 100 million monthly active users. Tubi offers the world's largest collection of Hollywood movies and TV shows, thousands of creator-led stories and hundreds of Tubi Originals made for the most passionate fans. Headquartered in San Francisco and founded in 2014, Tubi is part of Tubi Media Group, a division of Fox Corporation.</p> <p><em>We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, gender identity, disability, protected veteran status, or any other characteristic protected by law. We will consider for employment qualified ap