Principal Machine Learning Engineer

Tubi Tv; Toronto; Hybrid; CAD 130,000 - 170,000; Full time

Job summary

A leading streaming service provider is seeking a Principal Machine Learning Engineer for its Toronto office. This hybrid role emphasizes developing advanced recommendation systems and requires significant experience in machine learning. The ideal candidate will have a strong academic background in a related field and deep expertise in deep learning technologies along with a proven track record of building and optimizing machine learning pipelines.

Qualifications

• 10+ years of industry experience in Machine Learning.
• Ability to deep dive into individual components and systems.
• Solid understanding of statistical concepts.

Responsibilities

• Lead the design and implementation of recommendation systems.
• Build and deploy ML pipelines from data extraction to deployment.
• Continuously monitor and optimize performance of models.

Skills

Deep learning technologies

Recommendation systems

Data extraction and mining

Model training and testing

Performance evaluation metrics

Education

MSc or Ph.D. in a relevant field

Tools

TensorFlow

PyTorch

Job description

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.

About the Role

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.

We are seeking a highly skilled Principal Machine Learning Engineer to contribute to transformative projects in video personalization, with a focus on recommendation foundation modeling. In this role, you will design and implement advanced algorithms and systems to improve our personalization strategy. As a senior technical expert, you will tackle complex problems in machine learning at scale, collaborating closely with cross-functional teams to develop and optimize machine learning-driven solutions.

This is a hybrid role for our Toronto office.

What You'll Do

• Lead the design, development, and implementation of advanced recommendation systems and algorithms for a global audience.
• Conduct deep dives into algorithmic components and systems, ensuring that models are optimized for both performance and scalability across multiple regions and product areas.
• Build and deploy robust ML pipelines, including data extraction, feature development, model training, testing, and deployment.
• Continuously monitor, evaluate, and optimize the performance of deployed models, ensuring they meet business goals and provide high-quality user experiences.
• Work closely with Product, Engineering, and Content teams to align on product requirements, set expectations, and deliver machine learning-driven solutions that improve user engagement.

Your Background

• 10+ years of industry experience in Machine Learning.
• MSc or Ph.D. in Computer Science, Machine Learning, Statistics, Mathematics, or a related field.
• Expertise in deep learning technologies for recommendation systems, including experience with TensorFlow, PyTorch, or similar frameworks.
• Proficiency in building and deploying full-stack machine learning pipelines: data extraction, data mining, model training, feature development, testing, and deployment.
• Solid understanding of statistical concepts such as hypothesis testing, regression analysis, and performance evaluation metrics for machine learning.
• Ability to deep dive into individual components and systems, as well as understand the overall architecture of machine learning solutions.

Location note: This position is based in Toronto, Canada, with a hybrid schedule requiring at least two days per week onsite.

Equal Opportunity

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.