Senior ML Engineer

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 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.

ABOUT THE ROLE

We are seeking a Senior Machine Learning Engineer to join our growing team focused on the development and deployment of cutting-edge Large Language Models (LLMs) and Generative AI systems. In this role, you will be instrumental in building intelligent, scalable infrastructure and agentic workflows that power next-generation AI applications across FOX platforms.

You will work at the intersection of applied machine learning, generative modeling, and software engineering to design systems that can reason, adapt, and act autonomously based on complex inputs. This includes building LLM-based agents capable of task orchestration, context-aware decision-making, and dynamic interaction with tools and APIs.

If you're excited about pushing the boundaries of what LLMs can do—beyond chat—and enabling real-world, production-grade AI agents, this is the role for you.

A SNAPSHOT OF YOUR RESPONSIBILITIES

• Develop and fine-tune Large Language Models (LLMs) and foundational models to meet specific product and business goals

• Design and implement scalable machine learning pipelines for training, fine-tuning, and deploying LLMs

• Build and optimize agentic workflows, enabling LLMs to interface with external tools, APIs, and environments

• Collaborate with cross-functional teams including data scientists, engineers, and product leaders to embed AI capabilities into FOX applications

• Continuously evaluate and improve model performance, reliability, and efficiency in real-world use cases

• Stay up to date with the latest research in Generative AI, autonomous agents, and multi-modal learning

• Conduct rigorous testing, validation, and monitoring of deployed models in production environments

• Develop best practices, documentation, and internal tooling to support ongoing innovation and scalability

• Mentor junior engineers and help foster a high-performing, collaborative team culture

• Participate in system design and code reviews to uphold strong engineering standards

WHAT YOU WILL NEED

• Strong interest in sports, with a genuine enthusiasm for sports culture and content

• Proven experience developing and deploying machine learning models in production, with a focus on LLMs or generative AI

• Deep understanding of transformer architectures and techniques for fine-tuning and prompt engineering

• Strong proficiency in Python and ML frameworks like PyTorch, TensorFlow, or JAX

• Experience building agentic systems, including tool use, function calling, and multi-step reasoning

• Familiarity with vector databases, embeddings, and retrieval-augmented generation (RAG) techniques

• Hands-on experience with cloud platforms and ML infrastructure (e.g., AWS, GCP, Azure, or Databricks)

• Solid software engineering skills, including version control, CI/CD, and system design

• Ability to communicate complex technical concepts clearly to both technical and non-technical audiences

• A collaborative mindset and ability to thrive in a fast-paced, cross-functional environment

NICE TO HAVE, BUT NOT A DEALBREAKER

• Experience with autonomous agents, LangChain, OpenAI functions, or similar orchestration frameworks

• Familiarity with ethical and safety considerations in AI development

• Prior experience mentoring other engineers or leading projects

• Experience building multi-modal models (e.g., combining text, vision, or audio)

• Contributions to open-source ML libraries or published research in relevant areas

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