Head of Artificial Intelligence – Machine Learning
Gametime
full-time
Posted on:
Location Type: Remote
Location: Remote • 🇺🇸 United States
Visit company websiteSalary
💰 $311,950 - $367,000 per year
Job Level
Lead
Tech Stack
CloudMicroservices
About the role
- 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 Snowflake
Benefits
- Positive work culture
- Professional development opportunities
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
machine learningAI systemsMLOpsmodel trainingmodel deploymentmodel monitoringmodel evaluationsoftware architecturecloud computingmicroservices
Soft skills
leadershipcollaborationmentoringinnovationcommunicationtechnical excellencecuriositycross-disciplinary collaborationfeedback loopsstrategic alignment
Certifications
Bachelor’s in Computer ScienceMaster’s in Machine LearningPh.D. in Data Science