Associate Machine Learning Engineer

Tubi•San Francisco, CA

6d•$140,000 - $170,000•Hybrid

About The Position

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.

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
GPA Requirement: Minimum 3.0 GPA
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

Nice To Haves

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

Responsibilities

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