Machine Learning Engineer (Toronto)

OVERVIEW OF THE COMPANY

Fox Corporation

Under the FOX banner, we produce and distribute content through some of the world’s leading and most valued brands, including: FOX News Media, FOX Sports, FOX Entertainment, FOX Television Stations and Tubi Media Group. We empower a diverse range of creators to imagine and develop culturally significant content, while building an organization that thrives on creative ideas, operational expertise and strategic thinking.

JOB DESCRIPTION

AdRise is FOX's core ad tech platform, built to unify streaming and linear advertising across Tubi, FOX Sports, FOX News Media, and FOX Entertainment. Before AVOD became industry standard, AdRise helped power Tubi's growth from the ground up by developing real-time ad delivery and dynamic targeting infrastructure that scaled to serve millions. That same tech foundation is now fueling FOX's cross-portfolio monetization strategy.

We are rebuilding the ad stack for video by optimizing server-side delivery, building ML-driven targeting systems, and enabling content-personalized ad experiences that respond to what viewers actually watch. From real-time decisioning to data collaboration with AWS and Snowflake, we are creating a smarter, more dynamic ad tech ecosystem. The problems are complex, the visibility is high, and the platform is built for impact. If you want to work at the center of streaming monetization on systems that touch billions of impressions and shape the next generation of personalized advertising, this is your platform.

ABOUT THE ROLE
As an ML Engineer at AdRise, you will develop, deploy, and maintain scalable machine learning systems that directly impact monetization across FOX’s streaming and broadcast properties. This is a highly technical and hands-on role focused on building real-time inference pipelines, training infrastructure, and experimentation frameworks that fuel next-gen ad personalization and optimization. You’ll work in close collaboration with data science, engineering, and product teams to deploy ML solutions that operate under strict performance constraints.

A SNAPSHOT OF YOUR RESPONSIBILITIES

• Design and maintain machine learning pipelines for real-time ad decisioning
• Work with cross-functional teams to translate business goals into model solutions
• Implement experimentation systems (A/B testing, multi-armed bandits) to continuously optimize outcomes
• Collaborate on data integration with partners such as LiveRamp and TransUnion
• Contribute to the team’s MLOps infrastructure, from model training to deployment and monitoring
• Participate in code reviews, system design discussions, and sprint planning
• Conduct performance tuning and latency optimization for production ML systems

WHAT YOU WILL NEED

• 3+ years of hands-on machine learning or data engineering experience
• Proficiency with Python and ML frameworks such as TensorFlow or PyTorch
• Experience with real-time inference systems and streaming data architectures
• Familiarity with AWS, Spark, Kubernetes, and cloud-native development practices
• Background in deploying ML systems in production environments with measurable impact
• Solid understanding of ML experimentation, evaluation metrics, and optimization techniques

NICE TO HAVE, BUT NOT A DEALBREAKER

• Experience working in adtech, streaming, or real-time bidding environments
• Familiarity with yield optimization, media planning, or auction modeling
• Exposure to tools like MLflow, Snowflake, or Airflow

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