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Fox Television Stations

engineering opportunity

Machine Learning Engineer I

Rotate across two ML-focused teams to build, deploy, and monitor production machine learning models for streaming, sports, and news. Develop high-scale systems for video intelligence, search ranking, and monetization optimization.

New York, New York, United StateshybridFULL_TIME

Posted

About the role

What will you do at Fox Television Stations?

OVERVIEW OF THE COMPANY

JOB DESCRIPTION

FOX Forward Deployed is an 12-month rotational program that embeds early-career machine learning engineers inside the teams powering FOX’s biggest, most-watched moments.

You will complete two six-month deployments across AI-focused teams supporting streaming, sports, news, monetization, and enterprise data systems. You will contribute directly to production ML systems used at national scale.

This is not a research sandbox. Models must ship. Systems must scale.

You Build It. America Sees It.

ABOUT THE ROLE

As a Machine Learning Engineer in FOX Forward Deployed, you will rotate across two ML-focused teams embedded within core business units across Streaming, Sports, News, FOX One, and platform organizations. You will build, deploy, and monitor models operating inside live production systems.

From sports video intelligence and newsroom AI to ranking, retrieval, and monetization systems, you will work in high-visibility environments where model quality, latency, reliability, and deployment speed directly impact user experience and business performance.

You will operate in an AI-native environment leveraging platforms such as AWS SageMaker and Bedrock, Google Vertex AI, Databricks, Snowflake, ChatGPT, and Claude to accelerate experimentation and production delivery.

A SNAPSHOT OF YOUR RESPONSIBILITIES

Rotate across two ML-focused teams embedded within operating business units

Build, train, evaluate, and deploy production machine learning models

Work with large-scale, real-world datasets and live data streams

Integrate models into consumer-facing and enterprise systems

Monitor performance, detect drift, and iterate based on measurable outcomes

Operate under real constraints around latency, reliability, and scale

WHAT YOU COULD BUILD

Video Intelligence at Broadcast Scale: Develop computer vision systems that analyze live sports and news feeds, detect key moments, and generate AI-powered highlights and metadata used across FOX platforms.

Search, Ranking, and Retrieval Systems: Train and optimize recommendation and ranking models that determine what millions of viewers see across FOX properties.

Monetization Optimization Systems:​ Deploy predictive models that improve ad relevance, yield optimization, and engagement across streaming products.

Enterprise Data and AI Infrastructure: Contribute to ML pipelines and platform infrastructure that support retrieval, embeddings, and applied AI systems across consumer and enterprise applications.

WHAT YOU WILL NEED

Strong foundations in machine learning, statistics, or applied data science

Experience building and evaluating models through coursework, research, projects, internships

Proficiency in Python and common ML frameworks

Demonstrated use of AI-assisted tools to accelerate ML workflows

Ability to explain how you validated model quality using metrics, bias checks, reproducibility controls.

Curiosity about how models behave in production environments

Bias toward experimentation and measurable outcomes

Regular, on-site attendance at the workplace a minimum of 3 days per week is an essential function of the position. Selected candidate must be able to reliably meet this requirement.

FOX Forward Deployed is intentionally small and selective. Participants are expected to operate as contributing ML engineers from day one.

HOW WE EVALUATE BUILDERS

We evaluate builders by what they’ve shipped.

You will be asked to:

Share one ML artifact such as repository, demo, or paper

Explain the problem the model solved

Describe the evaluation metrics you chose and why

Detail one real constraint or tradeoff

Explain how you used AI tools and how you verified their outputs

NICE TO HAVE, BUT NOT A DEALBREAKER

Experience deploying models into production systems

Exposure to recommendation systems, ranking, or personalization

Familiarity with data pipelines or distributed systems

#DTC

#Ll-KD1

#Ll-Hybrid

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 $74,000.00-130,000.00 annually. This role is also eligible for an annual discretionary bonus, 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.

Which skills does this role require?

Machine LearningPythonStatisticsApplied Data ScienceModel DeploymentComputer VisionRanking and RetrievalAWS SageMakerGoogle Vertex AIDatabricksSnowflakeLLMsModel MonitoringBedrockChatGPTClaudeRetrievalMonetizationModel DriftLatencyReliabilityProduction MLAI-NativeEmbeddingsData ScienceAWSA/B Testing

Make your next move

Build a shortlist and prepare

Identify the requirements you can demonstrate, then choose examples from your work to discuss with the hiring team.

Review the responsibilities and requirements before adding an opening to your shortlist.

Role information can change. Confirm current details on the original application page.

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