Head of AI - Platforms

Zayo Group•Remote - Ontario, ON

1d•CA$300,000 - CA$315,000

About The Position

Zayo is seeking a Head of AI - Platforms to lead the strategic design, development, and deployment of AI-driven platforms and solutions across the organization. This role will focus on building scalable AI capabilities, modern MLOps practices, and enterprise-grade machine learning infrastructure to support innovation, automation, predictive analytics, and real-time decision systems. The Head of AI - Platforms will advance Zayo’s AI maturity, build a high-performing AI team, and partner with cross-functional stakeholders to deliver measurable business outcomes.

Requirements

10+ years of experience in AI, machine learning, data science, or advanced analytics, including hands-on experience building and deploying AI systems.
5+ years of experience leading AI, machine learning, data science, or engineering teams.
Expertise in transformer-based models such as GPT, BERT, T5, LLMs, computer vision, and multimodal AI.
Hands-on experience with AI frameworks such as TensorFlow, PyTorch, and JAX.
Experience designing and deploying large-scale AI systems in production environments.
Strong knowledge of MLOps, model monitoring, CI/CD for ML, data pipelines, feature stores, and cloud-based AI infrastructure.
Experience with AWS, Azure, or Google Cloud, as well as distributed training using GPUs or TPUs.
Demonstrated ability to translate business needs into AI strategies, technical roadmaps, and measurable outcomes.
Strong leadership, communication, stakeholder management, and cross-functional collaboration skills.
Knowledge of responsible AI, AI governance, model risk management, bias mitigation, and regulatory compliance.

Responsibilities

Develop and execute a comprehensive AI platform roadmap aligned with Zayo’s business objectives.
Lead the research, evaluation, and implementation of large-scale AI models, including LLMs, transformer-based models, computer vision, and multimodal AI.
Design and deploy AI solutions for predictive analytics, intelligent automation, operational optimization, and real-time decision-making.
Oversee the end-to-end AI lifecycle, including data engineering, model development, testing, deployment, monitoring, and continuous improvement.
Build and optimize scalable AI infrastructure using cloud platforms such as AWS, Azure, or Google Cloud, along with GPU and TPU-based distributed training environments.
Implement modern MLOps frameworks to support efficient model deployment, governance, observability, reliability, and performance monitoring.
Build, mentor, and lead a high-performing team of AI researchers, machine learning engineers, data engineers, and AI platform specialists.
Partner with engineering, network operations, product, data, security, compliance, and business teams to identify high-value AI use cases and ensure business alignment.
Establish responsible AI practices that address bias, fairness, transparency, model risk, security, and regulatory compliance.
Drive measurable business outcomes through AI-enabled improvements in efficiency, service reliability, customer experience, and operational decision-making.