Manager, AI Research

• →Leads and develops a high-performing team of AI research scientists and technical practitioners. Hires, coaches, evaluates, and develops crew while establishing high standards for technical excellence, collaboration, scientific rigor, and delivery. 

• →Provides technical leadership across applied AI research initiatives. Guides teams in framing complex problems, evaluating emerging approaches, designing experiments, developing models and prototypes, and determining which approaches warrant further investment or transition toward production. 

• →Builds strategic research partnerships. Works closely with the Head of AI R&D to support and advance Vanguard’s strategic research partnership with the University of Toronto, collaborating with faculty, researchers, and students to shape joint research initiatives, provide technical leadership, and translate promising academic research into enterprise capabilities. Builds additional internal and external partnerships, where appropriate, to accelerate innovation and bring relevant advances into Vanguard. 

• →Drives research from exploration to enterprise application. Works with research scientists, engineers, product teams, and business partners to move promising ideas through experimentation, validation, prototyping, technology transfer, and production adoption. 

• →Maintains technical depth in modern AI and machine learning. Engages directly with researchers on technical approaches, experimental design, model development, evaluation, and engineering trade-offs. Critically evaluates results and helps teams navigate complex technical challenges. 

• →Identifies and evaluates emerging AI capabilities. Assesses advances in areas such as generative AI, language models, agentic systems, reasoning, multimodal AI, AI evaluation, trustworthy AI, and machine learning to determine their applicability and readiness for Vanguard use cases. 

• →Establishes rigorous research and evaluation practices. Guides experimental design, benchmarking, model evaluation, reproducibility, and validation to ensure research conclusions are technically sound and capabilities meet appropriate standards before broader adoption. 

• →Partners with engineering and product teams to accelerate research-to-production. Helps define technical requirements, success criteria, architectural considerations, and transition plans needed to mature research prototypes into scalable enterprise capabilities. 

• →Balances innovation with practical delivery. Manages a portfolio of research initiatives across different maturity horizons, balancing exploratory work with near-term opportunities that can deliver measurable client, crew, or enterprise value. 

• →Advances responsible and secure AI development. Ensures research appropriately considers reliability, safety, security, privacy, robustness, explainability, and other responsible AI considerations throughout the research-to-production lifecycle. 

• →Influences AI strategy and technology decisions. Communicates research findings, emerging technology opportunities, technical risks, and recommendations to senior technical, product, and business leaders and helps inform broader AI investments and priorities. 

• →Participates in special projects and performs other duties as assigned. 

• Minimum of 5 years of relevant experience in artificial intelligence, machine learning, computer science, statistics, or a related technical field, including experience developing or leading advanced AI/ML solutions.  

• Demonstrated experience leading, mentoring, or managing research scientists, machine learning scientists, research engineers, or similarly technical talent.  

• Strong technical expertise in one or more areas of modern AI and machine learning, such as generative AI, language models, agentic AI, reinforcement learning, multimodal AI, model evaluation, trustworthy AI, or AI safety and security.  

• Demonstrated ability to move advanced technical work from research and experimentation into prototypes, reusable capabilities, products, or production systems.  

• Strong understanding of machine learning research and development practices, including experimental design, model development, evaluation, benchmarking, statistical reasoning, and reproducibility.  

• Ability to operate effectively in ambiguous environments, make sound technical decisions, and balance research exploration with practical delivery.  

• Demonstrated ability to collaborate across research, engineering, product, business, risk, and other multidisciplinary teams.  

• Strong communication skills with the ability to translate complex technical concepts and research findings for both technical and executive audiences.  

• Master’s degree in Computer Science, Machine Learning, Statistics, Mathematics, Engineering, or another related quantitative discipline, or equivalent combination of

• PhD in Computer Science, Machine Learning, Artificial Intelligence, Statistics, Engineering, or a related field.  

• Experience managing or technically leading senior scientists, researchers, or machine learning engineers.  

• Track record of research or advanced technical contributions demonstrated through deployed systems, publications, patents, open-source contributions, or other meaningful technical artifacts.  

• Experience transitioning AI/ML research into scalable production capabilities.  

• Experience partnering with engineering and product organizations on complex AI systems.  

• Experience working in financial services or another highly regulated or high-stakes environment. 

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.