Applied Machine Learning Scientist (Agents and Reasoning)

POSITION SUMMARY

As an Applied Machine Learning Scientist, Agents and Reasoning, you will be at the forefront of developing and implementing innovative advancements in agentic AI systems and reasoning architectures that enable impactful applications of the latest research breakthroughs. This role offers a unique opportunity to lead applied research by bridging state-of-the-art autonomous agents and reasoning-enabled models with practical applications across critical sectors such as health, industry, and responsible AI.

You will work alongside leading ML researchers, Applied ML Specialists, and research engineering labs to design and implement solutions powered by agent-based systems and reasoning frameworks with a focus on scalability, efficiency, and real-world impact. This role calls for both research engineering expertise and deep knowledge in AI reasoning and decision-making to advance the use of frontier ML systems including open-source tools and robust architectures that accelerate Vector’s mission.

The position encourages publishing applied research papers with a primary emphasis is on high-impact applications and real-world solutions. Candidates should have expertise in deploying ML systems, including experience with the latest research engineering approaches to optimize performance and enable flexible, adaptable solutions. This role presents an opportunity to lead and innovate in developing sophisticated agentic AI and reasoning systems that push boundaries in both technology and application.

KEY RESPONSIBILITIES

• Research and implement state-of-the-art techniques in AI agents, reasoning, and decision-making to solve real-world problems;
• Partner with researchers, other Applied ML Specialists, Vector professional staff, and collaboration partners to build demos, minimum viable products (MVP), and prototypes;
• Offer scientific advice regarding overall agentic AI application strategies and roadmaps;
• Provide scientific oversight for Vector-led or co-led efforts to prepare specific datasets or simulated environments for agent-based machine learning research;
• Act as the lead Vector specialist for health, industry, and responsible AI projects including contributing to and/or leading peer-reviewed publications;
• Design and deliver training and other initiatives to Vector staff and stakeholders focusing on increasing AI knowledge and building the organizational capacity to identify and implement agentic AI solutions;
• Serve as an expert and facilitate identification of experts among the Vector research community for external stakeholders (e.g., health and other sectors) to advise on emerging trends in AI agents, reasoning, and applications; and,
• Other duties as assigned.

SUCCESS MEASURES

• Develop and deploy agentic AI and reasoning-based models that address real-world challenges in health, industry, and responsible AI;
• Drive significant research engineering findings by optimizing, scaling, and deploying high-performance agent-based systems that demonstrate advancements in machine learning;
• Collaborate effectively with internal teams and external partners to create impactful prototypes, demos, and MVPs that highlight the practical value of agentic AI and reasoning;
• Contribute to training programs and knowledge transfer initiatives, enhancing AI literacy and capability across Vector and partner organizations;
• Provide thought leadership on emerging trends in agents, reasoning, and ML application strategies to align with and support Vector’s strategic objectives to influence broader research direction.

PROFILE OF THE IDEAL CANDIDATE

• Holds a PhD in computer science or computer engineering with a research focus on multi-agent systems, reasoning, or decision-making preferred;
• Demonstrated expertise in one or more of the following: planning, reinforcement learning, multi-agent coordination, symbolic/neurosymbolic reasoning, or autonomous decision-making as demonstrated by research publications and thought leadership at high impact conference and workshops venues;
• Demonstrated experience applying machine learning research to novel problems and data sets;
• Strong knowledge and experience in Python;
• Experience with software engineering and/or data engineering is considered an asset;
• Experience with parameter and architecture tuning of deep learning or reinforcement learning algorithms is considered an asset;
• Experience using open-source deep learning and agent frameworks (e.g., PyTorch, TensorFlow, JAX, Ray, or LangChain) is an asset.

At the Vector Institute, we are committed to driving excellence and leadership in Canada’s knowledge, creation, and use of AI to foster economic growth and improve the lives of Canadians. We strive for greater inclusion in the programs and culture that we build by welcoming and encouraging applications from all qualified candidates. This includes, but is not limited to, applicants who are Indigenous, 2SLGBTQIA+, racialized persons/visible minorities, women, and people with disabilities.

If you require an accommodation at any point throughout the recruitment and selection process, please contact hr@vectorinstitute.ai and we will happily work with you to meet your needs.