This organization works across emerging areas including Generative AI, Agentic AI, World Models and Large World Models (LWMs), Cognitive AI Architectures, Responsible AI, Knowledge Systems, and next-generation reasoning systems.
Role Overview
The Head of Applied AI Research & Development serves as the strategic leader responsible for operationalizing advanced AI research into enterprise-ready capabilities. This leader oversees multidisciplinary teams of applied AI/ML researchers, machine learning engineers, and AI platform specialists focused on delivering scalable AI solutions that directly impact Vanguard’s products, operations, and client experience.
The role combines technical leadership, product strategy, and organizational influence to accelerate AI adoption across the enterprise. Working closely with AI Research, AI Product, Engineering, Data, and business organizations, this leader establishes the frameworks, methodologies, and delivery mechanisms required to transform novel AI techniques into robust enterprise capabilities.
Success in this role requires balancing long-term innovation with near-term execution while building reusable AI platforms that continuously improve through enterprise knowledge, evolving data, and organizational learning.
Core Responsibilities
- Define and execute Vanguard’s Applied AI R&D strategy, aligning investments in applied AI, frontier research, and enterprise AI capabilities with long-term business objectives and competitive differentiation.
- Drive innovation across frontier AI domains, including foundation models, Large World Models (LWMs), world modeling systems, agentic AI, enterprise reasoning, cognitive AI architectures, and next-generation intelligent systems.
- Direct the development of applied AI architectures and research capabilities supporting reasoning, planning, simulation, knowledge representation, memory-aware intelligence, adaptive decision-making, and continuously evolving world-state models.
- Establish applied AI methodologies, standards, and evaluation frameworks that ensure AI systems are secure, governed, trustworthy, scalable, and capable of continuous improvement through enterprise data, feedback loops, and organizational learning.
- Partner with business, product, engineering, and external research organizations to accelerate adoption of AI capabilities, proof of concepts, build strategic partnerships, and translate emerging research into measurable business value.
- Lead multidisciplinary AI research, engineering, and platform teams responsible for translating advanced research into scalable, production-grade AI systems, products, and enterprise capabilities.
- Build and develop a world-class Applied AI organization by recruiting, mentoring, and growing high-performing talent while fostering a culture of technical excellence, experimentation, innovation, and responsible AI development.
Qualifications
- PhD or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Mathematics, Electrical Engineering, Cognitive Science, Management Science or a related discipline.
- 7+ years of experience leading Applied AI, Machine Learning, AI Engineering, or AI Platform teams within industry or research environments.
- Proven experience delivering applied AI capabilities which are repeatable across research or industry settings
- Deep expertise in large language models, foundation models, agentic AI, machine learning systems, reinforcement learning, retrieval systems, reasoning architectures, knowledge representation, or advanced AI applications.
- Experience designing AI systems capable of contextual understanding, sequential reasoning, adaptive decision-making, memory-aware architectures, or complex workflow orchestration
- Strong understanding of modern AI development lifecycles including experimentation, evaluation, deployment, monitoring, and continuous improvement
- Experience building enterprise AI solutions, model governance processes, evaluation frameworks, and scalable ML models
- Hands-on expertise with modern ML frameworks including PyTorch, TensorFlow, Hugging Face, distributed training, and cloud AI platforms
-Demonstrated ability to lead large, multidisciplinary AI initiatives spanning research, academic, business organizations across both industry or research environments
- Exceptional executive communication skills with experience influencing senior leadership and enterprise strategy
How We Work
Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.
Vanguard Toronto, Ontario, CAN Office
Toronto, Canada
