Vice President, AI Engineering at Vector Institute

Toronto, Ontario, Canada -

Full Time

Start Date

Immediate

Expiry Date

01 Jun, 26

Salary

285000.0

Posted On

03 Mar, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

AI Engineering Leadership, Multidisciplinary Team Management, AI/ML Systems, Scientific Computing, Cloud/Hybrid Compute Infrastructure, Open-Source AI/ML Frameworks, Machine Learning Methodologies, Technical Education Program Design, Sponsor Engagement, Leadership, Communication, Cross-functional Collaboration, Program Management, Knowledge Transfer, Public-Sector Innovation, Technical Speaking

Industry

Research Services

Description

Vice President, AI Engineering POSITION SUMMARY The Vice President, AI Engineering is a senior technical leader at the Vector Institute, responsible for guiding AI engineering efforts that enable world-class AI research and translate cutting-edge machine learning innovation into real-world societal and economic impact. This role oversees a diverse and multi-disciplinary group — including systems and infrastructure Specialists, Applied ML Scientists, ML Specialists, and technical product and program managers. As a key member of Vector’s senior leadership team, the VP serves as the operational leader of the AI Engineering workstream and represents the organization in Board of Directors' meetings, as well as acting as a trusted advisor for our internal as well as external stakeholders. The VP will ensure that researchers have access to best-in-class computing infrastructure and technical collaboration. The VP will also lead the Vector Institute’s AI engineering strategy and partnerships that accelerate AI adoption by industry sponsors, health sector organizations, and the broader public sector — without the need to build or maintain commercial products. KEY RESPONSIBILITIES * Develop strategy and lead execution for translating academic ML research output into usable code, tools, and techniques for external sponsors and partners; * Serve as a member of Vector’s senior leadership team, shaping long-term strategic planning and ensuring AI engineering alignment with organizational vision; * Represent the AI Engineering organization at Board of Directors’ meetings and lead Board-level engagements as needed; * Lead and scale a mission-driven, research-supported AI engineering function across infrastructure, ML engineering, and applied science; * Oversee a world-class AI computing environment, including collaboration with the Chief Information Office on deployment of scientific computing infrastructure, large-scale clusters, and hybrid cloud resources that support Vector’s research and training initiatives; * Attract and develop technical teams to support applied research and AI engineering efforts across diverse domains (e.g., health, finance, public sector); * Partner with researchers to identify promising innovations and create pathways for practical implementation; * Oversee technical program and product management for AI engineering initiatives aligned with Vector’s strategic objectives; * Facilitate sponsor engagement and knowledge transfer through micro-consulting, professional development programs, and hands-on technical internships; * Represent the Vector Institute as a senior technical spokesperson in public forums, international conferences, and stakeholder meetings; * Collaborate with internal and external stakeholders to develop and share reusable software components, proof-of-concept tools, and open-source contributions; * Guide the identification and development of intellectual property stemming from applied ML research; * Lead cross-functional business case development for major initiatives, aligning research, partnerships, productization, and societal impact (e.g., sector-scale programs like health); * Act as a trusted technical and strategic advisor to executive leadership on complex decisions and trade-offs; * Mentor engineering leaders and senior ICs, strengthening collaboration with researchers and enabling translation of research into deployed systems; * Own engineering budget strategy, balancing talent competitiveness, internal equity, and external market pressures; and, * Other related duties as assigned from time to time. KEY SUCCESS MEASURES * Vector’s AI Engineering teams are high-functioning, diverse, and delivering measurable impact in support of AI research and applied innovation; * Researchers and sponsors are equipped with the tools, infrastructure, and AI engineering collaboration needed to accelerate AI advancement; * Applied research outputs and tools are successfully adopted, adapted, or transferred to real-world organizations and use cases; and, * Sponsors perceive meaningful technical value through Vector's engagements, knowledge transfer programs, and internship offerings. PROFILE OF THE IDEAL CANDIDATE * Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field; advanced degree preferred; * 10+ years of experience in AI engineering leadership, with a track record of building and managing multidisciplinary technical teams; * Deep understanding of AI/ML systems and research workflows, ideally in a non-profit, academic, or applied research context; * Strong experience with scientific computing environments, cloud/hybrid compute infrastructure, and open-source AI/ML frameworks; * Demonstrated ability to partner with researchers to enable the application of complex machine learning methodologies in real-world settings; * Proven ability to design and implement programs that support technical education, internships, or sponsor engagement; * Excellent leadership, communication, and cross-functional collaboration skills; * Experience working at the intersection of research and engineering (e.g., research lab, AI institute, R&D unit) is preferred; * Familiarity with program management, knowledge transfer, or public-sector innovation initiatives is considered an asset; and, * A track record of speaking, publishing, or contributing to the broader AI community is considered an asset. TOTAL REWARDS: The expected salary for this position will be $228,000 - $285,000 per year, plus benefits if applicable. The final salary offer will reflect the successful candidate's experience, skills, and qualifications, in alignment with the Vector Institute's Compensation Policy and may differ from above. The Vector Institute’s Total Rewards approach extends beyond traditional compensation and benefits. Full-time employees are eligible for a comprehensive suite of supports that recognize and value employees, including vacation time, floater days, GRRSP, a Health Spending Account, a Summer Hours program, and flexible work arrangements. POSITION STATUS: This posting is for an existing vacancy. INCLUSION AND EQUAL OPPORTUNITY EMPLOYMENT: Vector believes AI powers possibility by advancing cutting-edge research and translating it into real-world impact through collaboration with research, industry, and government. Vector is committed to fostering a diverse and inclusive culture that reflects its values. The Vector Institute welcomes applications from all qualified candidates, including those who are Indigenous, 2SLGBTQIA+, racialized persons/visible minorities, women, and people with disabilities. If you require an accommodation at any stage of the recruitment or selection process, please contact hr@vectorinstitute.ai. The Vector Institute team will be happy to work with you to ensure your experience is as inclusive and accessible as possible. JOIN OUR COMMUNITY: Check out the Vector Institute’s Careers Page [https://vectorinstitute.ai/about/opportunities/open-positions-at-vector/] to explore open opportunities at Vector and Follow Vector on X [https://twitter.com/VectorInst], LinkedIn [https://ca.linkedin.com/company/vector-institute], and Bluesky [https://bsky.app/profile/vectorinstitute.ai] to stay connected with the latest developments in Ontario's AI ecosystem and the Vector Institute.

Responsibilities

The Vice President will guide AI engineering efforts to translate cutting-edge machine learning innovation into real-world impact, overseeing teams including infrastructure specialists, applied ML scientists, and technical product managers. Key duties involve developing strategy for translating academic research into usable code, overseeing the AI computing environment, and leading strategic partnerships to accelerate AI adoption across various sectors.