Machine Learning Engineer

Tubi is a global entertainment company and the most watched free TV and movie streaming service in the U.S. and Canada. Dedicated to providing all people access to all the world’s stories, Tubi offers the largest collection of on-demand content, including over 250,000 premium movies and TV episodes and over 300 exclusive originals. With a passionate fanbase and over 80 million monthly active viewers, the company is committed to putting viewers first with free, accessible entertainment for all.

About the Role:

The Machine Learning team at Tubi works on core algorithms that define the entire experience of its 33+ million users. We work on different areas such as recommendations, search, content understanding and ads. 

We are searching for a talented and motivated Machine Learning Engineer (Senior or Staff) to join our team to develop and improve our core search algorithms. In this role, you will take full ownership of tackling problems in Tubi’s search system, from algorithm research and development through prototyping, productionisation and experimentation. You will work with a variety of machine learning algorithms, from traditional models to cutting-edge LLM technologies, to address relevant problems. You need a strong background in machine learning, hands-on development skills to tackle some of the challenges in a fast-paced dynamic environment, and the ability to collaborate well in a cross-functional setting. The tech stack you will be working with is Spark, Scala, and Python, including PyTorch. 

Responsibilities:

• Design and build end-to-end machine learning models for search applications from analysis through production
• Conduct A/B tests to prove your ideas and share your learnings from the experiment results
• Collaborate with Product and backend engineering teams to ship high-impact features 

Requirements:

• 4+ years of experience (for senior) or 6+ years (for staff) in machine learning engineering with production systems using Scala, Python, and Apache Spark
• Experience owning recommendation or search models 
• MSc or PhD in Computer Science, Statistics, Applied Mathematics, Physics, or other technical field. PhD preferred.

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.

California Compensation:

Senior: ($162,000 - $232,000/year) + Bonus + Long Term Incentive Plan + Benefits

Staff: ($192,000 - $274,000/year) + Bonus + Long Term Incentive Plan + Benefits

#LI-MQ1

Tubi is a division of Fox Corporation, and the FOX Employee Benefits summarized here, covers the majority of all US employee benefits.  The following distinctions below outline the differences between the Tubi and FOX benefits:

• For US-based non-exempt Tubi employees, the FOX Employee Benefits summary accurately captures the Vacation and Sick Time.
• For all salaried/exempt employees, in lieu of the FOX Vacation policy, Tubi offers a Flexible Time off Policy to manage all personal matters.
• 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 the birth, adoption, surrogacy, or foster placement of a child. 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.
• For all full-time, regular employees, Tubi offers a monthly wellness reimbursement.

Tubi is proud to be an equal opportunity employer and considers qualified applicants without regard to race, color, religion, sex, national origin, ancestry, age, genetic information, sexual orientation, gender identity, marital or family status, veteran status, medical condition, or disability. Pursuant to the San Francisco Fair Chance Ordinance, we will consider employment for qualified applicants with arrest and conviction records. We are an E-Verify company.