Associate Machine Learning Engineer

Posted 5 Days Ago
Easy Apply
San Francisco, CA
In-Office
140K-170K Annually
Internship
News + Entertainment
The Role
As an Associate Machine Learning Engineer, you'll rotate through teams, building and deploying ML pipelines, contributing to projects that impact users, and developing expertise in various ML domains.
Summary Generated by Built In

About the Role: 

The Tubi Builder’s Program is designed for early-career professionals in Product, Engineering, Machine Learning, Design and Data Science who are passionate about building products that impact millions of users. Over the course of the program, participants will rotate through different machine learning teams - such as user recommendations and ranking, content understanding, and search ranking - to develop a well-rounded technical foundation. Builders gain hands-on experience across multiple areas of machine learning engineering teams in a fast-paced tech environment.

As a associate machine learning engineer, you will contribute to real-world projects, solve complex technical challenges, and collaborate with experienced engineers, product managers, and data scientists.

This program is ideal for candidates who are curious, adaptable, and excited to work across multiple machine learning and artificial intelligence domains while developing expertise in cutting-edge technology.

What You'll Do:

Throughout the program, you will:

  • Rotate across three machine learning engineering teams, gaining exposure to different technical disciplines
  • Build and deploy high-impact robust ML pipelines, including data extraction, feature development, model training, testing, and deployment
  • Ship production ML systems and features that impact millions of real users
  • Leverage cutting-edge AI technologies to build technical solutions at scale
  • Define success metrics and evaluate impact via offline and online experiments
  • Monitor, evaluate, and optimize the performance of deployed models
  • Work closely with Product, Engineering, and Data Science teams to align on product requirements, set expectations, and deliver machine learning-driven solutions that improve user engagement
  • Participate in mentorship, technical training, and networking events throughout the program
  • Engage in engineering-wide initiatives to improve processes and technical standards

Qualifications: 

Minimum Requirements:

  • Master’s or PhD degree in Computer Science or a related field with emphasis on Machine Learning
  • Strong coding proficiency in at least one programming language (e.g., Python, Java, C++, Go)
  • Solid understanding of computer science fundamentals, algorithms, and system design
  • Demonstrated understanding and interest in machine learning engineering
  • Passion for problem-solving, collaboration, and building scalable systems
  • Strong communication skills and ability to work in a team-oriented environment

Preferred Qualifications:

  • Work Experience: Up to three years of combined professional experience, including internships
  • Professional experience (e.g. internship, research assistantship or work experience) in some software engineering areas (infrastructure, machine learning, or front-end development)
  • Familiarity with cloud platforms (AWS, GCP, Azure) and DevOps tools.
  • Experience with machine learning
  • Demonstrated curiosity and interest in an engineering area through research, past jobs, open-source contributions, or side projects

Program Eligibility Requirements:

  • GPA Requirement: Minimum 3.0 GPA
  • Application Deadline: 2/15/2026
  • Program Timeline: Minimum 18 month commitment, starting Aug 2026, after which successful participants will have the opportunity to transition into non-rotational full-time roles
  • Work Schedule: Full-time, hybrid in San Francisco with office day requirements
  • Work Authorization: Must have U.S. work authorization; we are unable to sponsor visas for this program.
  • Committed and available to work for the entire 18 month length of the program

About the Program:

Our Machine Learning Engineering Rotational Program is structured to accelerate the careers of early-stage engineers by providing them with hands-on experience in multiple technical domains. Through structured rotations, mentorship, and targeted development, participants will gain technical depth and breadth, preparing them for a non-rotational engineering role.

By the end of the program, you will:

  • Have experience across multiple machine learning engineering disciplines.
  • Develop technical and leadership skills.
  • Build a strong professional network within the organization.

#LI-Hybrid #LI-CN1

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 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.

High cost labor markets such as but not limited to Los Angeles, New York City, and San Francisco
$140,000$170,000 USD

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 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.
  • For all full-time, regular employees, Tubi offers a monthly wellness reimbursement.
About Tubi:

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.

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 applicants with criminal histories consistent with applicable law.

Top Skills

AWS
Azure
C++
GCP
Go
Java
Python
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The Company
HQ: San Francisco, CA
504 Employees
Year Founded: 2014

What We Do

Tubi, a division of FOX Entertainment, is an ad-supported video-on-demand service with more than 40,000 movies and TV shows in the U.S., including a growing library of Tubi Originals, 145+ local and live news, sports and entertainment channels, and 400+ entertainment partners, featuring content from every major Hollywood studio. Tubi gives fans of film, television, news and sports an easy way to discover new content that is completely free.

Tubi is available in the U.S. on Android and iOS mobile devices, Amazon Echo Show, Google Nest Hub Max, Comcast Xfinity X1, Cox Contour, and on connected television devices such as Amazon Fire TV, Vizio TVs, LG TVs, Sony TVs, Samsung TVs, Roku, Apple TV, Chromecast, Android TV, PlayStation 4 & 5, Xbox One & Series X|S, and soon on Hisense TVs globally. Consumers can also watch Tubi content on the web at www.tubi.tv.

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