Versant

media

SeniorAIEngineer

$155–215k ~AI est. Englewood Cliffs, New Jersey, United States FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for mid candidates.

The Brief

“Senior AI Engineer at Versant. Skills: AI/ML, Generative AI, Semantic search, MLOps. Design intelligent systems. Build intelligent systems”

What You'll Achieve.

Enhance content performance; Improve editorial productivity; Improve audience experience

Industry & Context.

media
Problems you'll solve

Problem-solving; Debugging; Analytical; Troubleshooting

What They're Looking For.

Must Have

software engineering and applied AI/ML experience, large-scale, high-availability environments, Proficiency in Python and Java, Hands-on experience with LangChain, Experience integrating and evaluating AI models, Deep understanding of prompt engineering, Experience with AWS cloud services

Nice to Have

Experience in media industry, Experience in publishing industry, Experience in streaming industry, Experience in advertising industry, Experience in digital content industry, Familiarity with content modeling, Familiarity with taxonomies, Familiarity with metadata, Familiarity with editorial workflows, Familiarity with personalization, Familiarity with recommendations, Experience with MLOps, Experience with model monitoring, Experience with feature pipelines, Experience with experimentation, Experience with A/B testing, Experience with offline/online evaluation frameworks, Master’s degree in computer science, Master’s degree in machine learning, Master’s degree in data science

What You'll Do.

Design intelligent systems

Build intelligent systems

Operationalize intelligent systems

Enhance content discovery

Enhance personalization

Enhance editorial workflows

Enhance audience experiences

Build services for RAG

Build services for semantic search

Build services for model integration

Build services for prompt orchestration

Build services for evaluation

Build services for production AI workflows

Contribute through engineering

Contribute through applied AI expertise

Provide architectural input

Build reliable products

Build measurable products

Build maintainable AI/ML products

Partner with product teams

Partner with data science teams

Partner with editorial teams

Partner with analytics teams

Partner with design teams

Define AI requirements

Define ML requirements

Conduct architecture reviews

Conduct design discussions

Promote engineering best practices

Promote ML best practices

Promote responsible AI best practices

Identify systemic team issues

Solve systemic team issues

Participate in AI architecture conversations

Guide AI architecture conversations

Participate in model capabilities conversations

Guide model capabilities conversations

Participate in search relevance conversations

Guide search relevance conversations

Participate in media industry trends conversations

Guide media industry trends conversations

Champion user-first mindset

Advocate for AI solutions

Improve content performance

Improve editorial productivity

Improve audience experience

Design AI/ML services

Deliver AI/ML services

Support content intelligence use cases

Support semantic search use cases

Support recommendations use cases

Support automation use cases

Support generative AI use cases

Build production services

Maintain production services

Develop AI applications

Develop orchestration workflows

Integrate large language models

Integrate embedding models

Integrate multimodal models

Integrate domain-specific AI services

Design prompt engineering strategies

Design prompt templates

Design evaluation workflows

Deploy ML-enabled applications

Monitor ML-enabled applications

Secure ML-enabled applications

Scale ML-enabled applications

Implement vector search

Implement retrieval-augmented generation

Promote test coverage

Promote model evaluation

Promote secure development

Promote responsible AI practices

Drive adoption of AI platform patterns

Evolve shared ML engineering capabilities

Debug model integrations

Profile model integrations

Optimize model integrations

Debug inference workflows

Profile inference workflows

Optimize inference workflows

Debug search relevance

Profile search relevance

Optimize search relevance

Collaborate with SREs

Collaborate with platform teams

Ensure AI services are observable

Ensure AI services are resilient

Ensure AI services are production-ready

Scope large AI initiatives

Break down model problems

Break down data problems

Break down platform problems

Communicate timelines

Communicate model limitations

Communicate operational tradeoffs

Balance competing priorities

Support team in achieving timelines

Maintain code quality

Maintain model quality

Maintain sustainable velocity

Define cohesive AI-powered experiences

Deliver cohesive AI-powered experiences

Participate in technical hiring

Help scale AI engineering capabilities

Help scale ML engineering capabilities

Help scale platform engineering capabilities

Create documentation for AI architectures

Create documentation for model integrations

Create documentation for prompt strategies

Create documentation for evaluation results

Create documentation for operational runbooks

Maintain documentation for AI architectures

Maintain documentation for model integrations

Maintain documentation for prompt strategies

Maintain documentation for evaluation results

Maintain documentation for operational runbooks

Communicate technical decisions

Communicate model behavior

Communicate tradeoffs

Participate in post-incident reviews

Participate in model quality reviews

Participate in cross-team discussions

How You'll Work.

Team & Collaboration

Product teams; Data science teams; Editorial teams; Analytics teams; Design teams; SREs; Platform teams; Cross-functional teams

Communication Scope

Technical decisions; Model behavior; Risks; Tradeoffs; Executive presentations; Technical documentation

Process & Methodology

Scoping initiatives, Breaking down problems, Balancing priorities

Full Job Description

VERSANT is a leading force in news, sports and entertainment - home to iconic and trusted brands that inspire, inform, and delight audiences. Our unique combination of content, technology and services enriches the cultural fabric, igniting passions, sparking conversations, and connecting people to what they love most. As an independent, publicly traded company, VERSANT brings together powerhouse cable networks - including USA Network, CNBC, MS NOW (formerly MSNBC), Oxygen, E!, SYFY, and Golf Channel - with dynamic digital and direct-to-consumer brands such as Fandango, Rotten Tomatoes, GolfNow, GolfPass, and SportsEngine. Together, these businesses reflect our commitment to delivering exceptional experiences across every screen and service. VERSANT is an industry-changing media company fueled by innovation and an entrepreneurial spirit. With a strong foundation and a forward-looking vision, VERSANT empowers creativity, embraces change, and drives connection in an ever-evolving world. As a Senior AI/ML Engineer on the AI Experience team, you will play a critical role in designing, building, and operationalizing intelligent systems that enhance content discovery, personalization, search, editorial workflows, and audience experiences across VERSANT digital platforms. You’ll work with Python, Java, LangChain, AWS, OpenSearch, and a range of modern AI models to deliver scalable machine learning and generative AI capabilities. You will build services that support retrieval-augmented generation, semantic search, model integration, prompt orchestration, evaluation, and production-grade AI workflows. You will contribute not only through strong engineering and applied AI expertise, but also through mentorship, architectural input, responsible AI practices, and a commitment to building reliable, measurable, and maintainable AI/ML-enabled products. What We Value Senior AI/ML Engineers at VERSANT go beyond model experimentation. They turn ambiguous business needs into practical

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