Machine Learning Engineer (L1)

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

Under the FOX banner, we produce and distribute content through some of the world’s most iconic and 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 deliver culturally impactful content, while fostering an environment that thrives on innovation, creativity, and strategic execution.

ABOUT THE ROLE

We’re looking for a Data Science & Machine Learning Engineer I to join our Personalization & Recommendations (PNR) team for our Direct-to-Consumer (DTC) streaming platform. This is an entry-level role for someone with 1–2 years of experience who is eager to work on real-world recommendation systems and contribute across the ML model lifecycle—from research and training to deployment and experimentation.

You’ll work with senior ML engineers and data scientists to develop candidate generation & ranking models, semantic re-rankers, and AI-driven pipelines that drive personalized experiences such as homepage ranking, watch-next suggestions, Short Form Content and intelligent search. You will also gain exposure to LLMs and AI agents for automating ML workflows and experimentation setups.

This is a great opportunity to build hands-on skills in production ML, A/B testing, version control, and cloud-native ML infrastructure like Databricks.

A SNAPSHOT OF YOUR RESPONSIBILITIES

• Explore and analyze user data to derive meaningful insights for model training

• Research, train, and evaluate ML models (ranking, re-ranking, retrieval) for content personalization

• Contribute to model versioning, tracking, and deployment pipelines using tools like MLflow and Databricks

• Set up and monitor A/B tests to measure the performance of different model variants and strategies

• Assist in building workflows using LLMs and AI agents for automating repetitive or manual tasks in data preparation, feature engineering, and experimentation

• Implement model inference logic in production environments under the guidance of senior engineers

• Collaborate with cross-functional teams to integrate model outputs into API services and end-user experiences

WHAT YOU WILL NEED

• 1–2 years of experience in machine learning, data science, or a related field (internships and academic projects welcome)

• Strong foundation in machine learning concepts, especially around recommendation systems or information retrieval

• Hands-on experience with Python and ML libraries like scikit-learn, PyTorch, TensorFlow, or Transformers

• Familiarity with SQL and data wrangling in environments like Spark or Databricks

• Exposure to model training workflows, versioning practices, and experiment tracking (e.g., with MLflow)

• Understanding of A/B testing frameworks and performance evaluation metrics (e.g., NDCG, CTR, recall)

• Curiosity and a growth mindset around LLMs, semantic models, and the use of AI agents in workflow automation

• Strong collaboration and communication skill

NICE TO HAVE, BUT NOT REQUIRED

• Experience using Databricks, AWS SageMaker, or similar ML platforms

• Familiarity with vector search engines (e.g., FAISS, Vespa) or semantic ranking

• Exposure to LangChain, LlamaIndex, or similar frameworks for building AI agents or pipelines

• Knowledge of MLOps principles and basic CI/CD for ML workflows

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.