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About the Role
Build and develop high-performing technical teams, identify promising applications of emerging AI methods, and partner closely with engineering, product, technology, and business teams to translate research advances into scalable, responsible, and differentiated capabilities.
Responsibilities
- Lead and develop a high-performing team of AI research scientists and technical practitioners.
- Hire, coach, evaluate, and develop crew while establishing high standards for technical excellence, collaboration, scientific rigor, and delivery.
- Provide technical leadership across applied AI research initiatives.
- Guide 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.
- Build strategic research partnerships with institutions like the University of Toronto, collaborating with faculty, researchers, and students.
- Shape joint research initiatives, provide technical leadership, and translate promising academic research into enterprise capabilities.
- Build additional internal and external partnerships to accelerate innovation and bring relevant advances into the company.
- Drive research from exploration to enterprise application, working with research scientists, engineers, product teams, and business partners.
- Move promising ideas through experimentation, validation, prototyping, technology transfer, and production adoption.
- Maintain technical depth in modern AI and machine learning, engaging directly with researchers on technical approaches, experimental design, model development, evaluation, and engineering trade-offs.
- Critically evaluate results and help teams navigate complex technical challenges.
- Identify and evaluate emerging AI capabilities, assessing advances in areas such as generative AI, language models, agentic systems, reasoning, multimodal AI, AI evaluation, trustworthy AI, and machine learning.
- Determine the applicability and readiness of AI advancements for company use cases.
- Establish rigorous research and evaluation practices, guiding experimental design, benchmarking, model evaluation, reproducibility, and validation.
- Ensure research conclusions are technically sound and capabilities meet appropriate standards before broader adoption.
- Partner with engineering and product teams to accelerate research-to-production, helping define technical requirements, success criteria, architectural considerations, and transition plans.
- Mature research prototypes into scalable enterprise capabilities.
- Balance innovation with practical delivery by managing a portfolio of research initiatives across different maturity horizons.
- Balance exploratory work with near-term opportunities that can deliver measurable client, crew, or enterprise value.
- Advance responsible and secure AI development, ensuring research appropriately considers reliability, safety, security, privacy, robustness, explainability, and other responsible AI considerations.
- Influence AI strategy and technology decisions by communicating research findings, emerging technology opportunities, technical risks, and recommendations to senior leaders.
- Inform broader AI investments and priorities.
- Participate in special projects and perform other duties as assigned.
Requirements
- Minimum of 5 years of relevant experience in artificial intelligence, machine learning, computer science, statistics, or a related technical field.
- 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 education and experience.
Skills
- Artificial intelligence
- Machine learning
- Computer science
- Statistics
- Generative AI
- Language models
- Agentic AI
- Reinforcement learning
- Multimodal AI
- Model evaluation
- Trustworthy AI
- AI safety and security
- Experimental design
- Model development
- Benchmarking
- Statistical reasoning
- Reproducibility
- Collaboration
- Communication
Location
- Hybrid
Work Type
- Hybrid
- Full-time
Experience Level
- Minimum 5 years of relevant experience
- Experience leading, mentoring, or managing technical talent
Education Level
- Master's degree in Computer Science, Machine Learning, Statistics, Mathematics, Engineering, or another related quantitative discipline, or equivalent combination of education and experience.
- PhD in Computer Science, Machine Learning, Artificial Intelligence, Statistics, Engineering, or a related field.
About the Company
- 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.