Head of Artificial Intelligence – Machine Learning

Job Description:• 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.• 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. • 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. • 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. Requirements:• 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 SnowflakeBenefits:• Positive work culture• Professional development opportunities Apply tot his job