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

Job Duties:

As part of the Data Engineering team, Fox Cable Network Services, LLC seeks a Data Scientist (MLOps Engineer) to focus on deploying, managing, and scaling machine learning models within Fox’s AWS and Databricks environments. Play a crucial role in ensuring Fox’s ML (machine learning) models are deployed reliably, maintained efficiently, and deliver value across the organization. Work effectively with multiple internal stakeholders across diverse groups such as Fox Sports, Fox News Media, Fox Entertainment, and Fox Television Stations to support a wide array of Data Science and Data Engineering initiatives. Specific duties include: 1) Design, implement, and maintain robust, scalable ML pipelines for the production and deployment of machine learning models. 2) Collaborate closely with other data scientists, data engineers, and DevOps to ensure seamless integration and performance of models in AWS and Databricks environments. 3) Build automated workflows for model deployment, monitoring, and retraining, ensuring high availability and reliability. 4) Develop processes for tracking, logging, and versioning of models to support reproducibility and auditability. 5) Implement monitoring solutions to track model performance and data drift, providing insights to maintain and improve model quality over time. 6) Troubleshoot, debug, and optimize ML pipelines to improve efficiency and reduce latency. 7) Stay updated with the latest advancements in MLOps tools and practices, ensuring that Fox infrastructure remains cutting-edge and future-ready. Telecommuting permitted from any location in the U.S.

Job Requirements:

Requires a Master’s degree in Data Science, Computer Science, Information Technology, Engineering or related field, plus two (2) years of experience in data science or related experience in MLOps/DevOps, including experience deploying and maintaining ML models in production; and building CI/CD pipelines for ML models using tools such as Git and Jenkins.

Specific skills: Also requires experience or knowledge in the following: 1) Experience in ML frameworks such as Tensor Flow, Py Torch and scikit-learn; 2) Experience in SQL, Python, Docker, and Kubernetes; 3) Knowledge of monitoring and logging tools used to track model performance and data quality such as Prometheus, Grafana and CloudWatch; 4) Experience with A/B testing and experiment design; 5) Experience with product analytics and working with event-level data; and 6) Experience in Databricks and AWS services such as S3, EC2, Sage Maker and Lambda

Any level of experience or knowledge in the specific skills is acceptable.

Telecommuting permitted from any location in the U.S.

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.

Pursuant to state and local pay disclosure requirements, the pay rate/range for this role, with final offer amount dependent on education, skills, experience, and location is $146,680.41-161,348.00 annually. This role is also eligible for various benefits, including medical/dental/vision, insurance, a 401(k) plan, paid time off, and other benefits in accordance with applicable plan documents. Benefits for Union represented employees will be in accordance with the applicable collective bargaining agreement.

View more detail about FOX Benefits.