Associate Machine Learning Engineer
@ Tubi
Summary
About the Company
Company Name: Tubi
Industry: Entertainment
Benefits
Medical, dental, vision insurance, 401(k) plan, paid time off, flexible time off policy, parental leave program, monthly wellness reimbursement, annual discretionary bonus, long-term incentive plan
Job Description
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 Program:
Our Tubi Builders Machine Learning Engineering 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 full-time engineering roles.
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.
About the Role:
The Rotational Program - Machine Learning Track is designed for early-career engineers and recent college graduates looking to gain hands-on experience across multiple areas of machine learning engineering teams in a fast-paced tech environment. 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.
As an 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. By the end of the program, participants will have the opportunity to transition into a full-time machine learning engineering role, equipped with the experience and skills to drive innovation.
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
- Design, develop, and optimize scalable systems, infrastructure, and applications
- Work with programming languages such as Python, Java, C++, or Go
- Apply computer science fundamentals in data structures, algorithms, machine learning, recommender systems and system design
- Debug, troubleshoot, and improve system performance and reliability
- Collaborate with cross-functional teams to launch and improve products
- Gain experience in cloud computing, DevOps, CI/CD pipelines, and distributed systems
- 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 professional and non-internship experience post-graduation
- 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, side projects
Program Eligibility Requirements:
- GPA Requirement: Minimum 3.0 GPA
- Application Deadline: 3/11/2025
- Program Timeline: Minimum 18-month commitment, starting Aug 2025, after which successful participants will have the opportunity to transition into 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
Responsibilities
Qualifications
Education Level: Master's Degree