MERCY COLLEGE is hiring: Machine Learning Engineer, FOX Forward Deployed in vill

Machine Learning Engineer, FOX Forward Deployed

Recruitment began on April 14, 2026

Job listing expires on May 15, 2026

Job Description

FOX Forward Deployed is a 12‑month rotational program that immerses early‑career machine learning engineers in the teams driving 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, contributing directly to production ML systems used at a 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, impacting user experience and business performance.

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

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 trade‑off
  • Explain how you used AI tools and how you verified their outputs

Nice to Have, But Not a Deal‑Breaker

• Experience deploying models into production systems
• Exposure to recommendation systems, ranking, or personalization
• Familiarity with data pipelines or distributed systems

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 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 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.

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