Head of Artificial Intelligence & Machine Learning

About Us: Live experiences help people cross today’s digital divide and focus on what truly connects us – the here, the now, this once-in-a-lifetime moment that’s bringing us together. To fulfill Gametime’s mission of uniting the world through shared experiences, we make it easy for people to discover and access the live experiences that matter most.   With platforms on iOS, Android, mobile web and desktop supporting more than 60,000 events across the US and Canada, we are reimagining the event ticket industry in order to move at the speed of life.

The Role:

Gametime is building the foundation for AI-driven user experiences — from intelligent recommendations and semantic search to automated decision systems and generative interfaces that redefine how fans discover and engage with live events.

The Head of AI & Machine Learning will lead the technical and organizational buildout of GT’s AI and ML foundations across our ML Platform, AI Platform, and Modeling teams.

This is a critical technical leadership role — responsible for shaping how GT powers next-generation user experiences through scalable infrastructure, production-grade ML, and large language model (LLM) integrations. The ideal candidate is a hands-on, execution-focused leader who can architect systems, build high-impact teams, and evolve our AI strategy as capabilities grow.

 

What you will work on

Build the Foundation

• Design and build GT’s AI and ML platform ecosystem, spanning ML Platform, AI Platform, Data Platform, and applied modeling layers that power personalization, recommendations, and intelligent automation.
  
  
• Establish systems for model training, deployment, monitoring, and evaluation at scale, ensuring reliability and repeatability across teams.
  
  
• Lead the implementation of LLM and agentic frameworks, including vector embeddings, evaluation pipelines (evals), and orchestration systems to support both product and internal AI capabilities.
  
  

Technical Leadership

• Architect and oversee the development of production-grade AI systems — from experimentation to live deployment.
  
  
• Partner with engineering and data teams to integrate ML and generative AI models into GT’s platform and consumer experiences.
  
  
• Champion MLOps best practices, enabling fast iteration and safe deployment cycles for data and model pipelines.
  
  

Strategic Direction & Collaboration

• Define and execute GT’s AI/ML roadmap, ensuring alignment with company vision and product goals.
  
  
• Collaborate cross-functionally with product, data, and infrastructure leaders to identify opportunities for AI innovation in personalization, discovery, pricing, and content generation.
  
  
• Partner with leadership to develop ethical AI standards, governance frameworks, and performance metrics that scale responsibly.
  
  

Team Building & Mentorship

• Recruit, mentor, and grow a world-class team of ML engineers, data scientists, and AI platform developers.
  
  
• Foster a culture of technical excellence, curiosity, and cross-disciplinary collaboration.
  
  
• Establish strong feedback loops between research, engineering, and product to accelerate innovation.
  
  

 

Experience you bring 

Required

• Bachelor’s, Master’s, or Ph.D. in Computer Science, Machine Learning, Data Science, or a related field.
• 8–12+ years of experience in AI/ML engineering, including 3–5 years in technical leadership roles.
• Strong background in machine learning capabilities. For example, this could include product recommendation engines, ranking problems, or dynamic pricing systems, etc
• Experience influencing platform development for providing foundational machine learning components for data scientists to deliver into production
• Deep knowledge of software architecture and engineering best practices, especially modern cloud computing stacks for deploying machine learning and microservices at scale especially on Snowflake
• Strong background in machine learning capabilities. For example, this could include product recommendation engines, ranking problems, or dynamic pricing systems, etc
• Experience influencing platf