Machine Learning Engineer

OVERVIEW OF THE COMPANY

JOB DESCRIPTION

OVERVIEW OF THE COMPANY

Fox Corporation is home to industry-leading brands including FOX News Media, FOX Sports, FOX Entertainment, FOX Television Stations, and Tubi Media Group. We combine innovative technology, deep data insights, and world-class content to shape the future of digital entertainment. Our DTC platforms are built to deliver highly personalized, scalable user experiences to millions of global users.

ABOUT THE ROLE

FOX Corporation is looking for a SDE (L2), ML / Senior Engineer, MLto join the Personalization & Recommendations (PnR)team and help drive the evolution of personalized content discoveryacross our streaming products. In this role, you’ll be a hands-on contributorresponsible for designing, building, and deploying ML models for recommendations, ranking, and semantic search, and ensuring they evolve through continuous learning and experimentation.

You will work at the intersection of ML model development, production engineering, and data-driven experimentation, collaborating with cross-functional teams to ensure scalable, performant, and personalized experiences. This role is ideal for engineers who have built and iterated on production-grade personalization systemsand thrive on both deep technical challenges and business impact.

A SNAPSHOT OF YOUR RESPONSIBILITIES

• Design and build scalable recommendation and personalization models(ranking, re-ranking, user embeddings, semantic retrieval)

• Own the full model lifecycle: from data preparation, training, and evaluation, to versioning, deployment, and monitoring

• Develop and maintain continuous training loopsand model refresh strategiesfor dynamic personalization

• Set up and interpret A/B experimentsto optimize model performance and user engagement

• Collaborate with data engineers, MLOps teams, and product managers to ensure models integrate seamlessly into real-time and batch inference pipelines

• Leverage platforms like Databricks, MLflow, and feature storesto streamline model experimentation and reproducibility

• Apply LLMs and AI agentsto improve personalization workflows and accelerate ML development pipelines

• Contribute to architecture decisions for personalization services and model serving infrastructure

• Mentor and provide technical guidance to junior data scientists and ML engineers, conducting code reviews, sharing best practices, and supporting their growth in areas such as model development, experimentation, and productionization

WHAT YOU WILL NEED

• At least 3-7 years of experience in machine learning, applied data science, or related fields, with a strong focus on recommendation systems or personalization

• Demonstrated experience in developing and deploying ML modelsinto production environments

• Deep understanding of ranking systems, user behavior modeling, and evaluation techniques (e.g., NDCG, AUC, MAP, CTR)

• Proficient in Pythonand ML libraries like PyTorch, TensorFlow, and frameworks such as Transformers or LightGBM

• Experience with Databricks, Spark, or similar big data platforms for large-scale model training and data processing

• Familiarity with model versioning, feature stores, experiment tracking, and MLflow

• Strong grasp of A/B testing design, analysis, and interpreting results for iterative model improvements

• Experience with LLM-based pipelines, semantic search, or vector similarity systems(e.g., FAISS, Vespa) is a plus

• Comfort working in cloud-native environments such as AWS or GCP

NICE TO HAVE, BUT NOT REQUIRED

• Experience using or building AI agents, LangChain, or workflow automation frameworksfor model experimentation

• Exposure to real-time inference systemsand streaming architectures (Kafka, Flink)

• Experience working on personalization systems at scale, particularly for high-traffic applications or live events Contributions to open-source ML tools or research in personalization-related fields

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.