Architect, Machine Learning

About Kinaxis

Are you looking to join an innovative, market-leading company where you can truly elevate your career? At Kinaxis we are serious about culture, we are serious about technology, we are serious about customers, and we are serious about not taking ourselves too seriously. If you are looking to be part of an incredible growth story, then we might just be the place for you In 1984, we started out as a team of three engineers. Today, we have grown to become a global organization with over 2000 employees around the world, 6 global office and a best-in-class HQ in Ottawa, Canada. As winners of several Top Employer awards globally, we are proud to work with our customers and employees towards solving some of the biggest challenges facing supply chains today.

Location

Ottawa and Toronto, CA - Hybrid Other Canadian and USA locations - Remote

About The Team

The AI team is responsible for advancing machine learning solutions in the supply and demand space across industries such as Retail, Consumer Packaged Goods, and Life Sciences. Our work spans forecasting, optimization, replenishment, recommendation, explainability, and emerging AI techniques that help customers solve complex, real-world planning challenges.

What makes this team unique is that we operate at the intersection of applied research, product innovation, and customer impact. We explore new methods, develop novel approaches, and turn them into practical capabilities that can shape the future of the Kinaxis platform. This is a team for people who want to work on meaningful problems, push the boundaries of applied AI in real business settings, and see their ideas influence products used by customers around the world.

Machine Learning Architect

I n this role, you will work across research, product, and engineering boundaries to apply machine learning and Generative AI to complex supply chain problems. You will contribute through technical leadership and hands-on work, using modern tools and agents to explore ideas, develop early systems, and help guide what should move toward productization.

Vacancy Status

This is an existing job vacancy

What you will do

You bring deep expertise in machine learning and applied AI, and you are energized by turning emerging techniques into practical solutions for real customer problems. You are comfortable working through ambiguity, exploring new approaches, and building early systems that demonstrate clear value.

You bring broad technical leadership across teams while remaining hands-on in applied research and innovation. You stay closely attuned to the rapidly evolving AI landscape, actively exploring and experimenting with emerging techniques, tools, and approaches to identify where they can create real product value. You have a knack for spotting high- leverage opportunities, cutting through complexity, and turning novel ideas into practical advances. You guide major technical decisions, identify opportunities for differentiation, and help translate new ideas into future product capabilities.

You will work closely with product and engineering teams to ensure ideas are grounded in real-world constraints and can evolve into enterprise-grade software. You balance innovation with pragmatism and bring a strong focus on customer impact.

You will also mentor others across the organization and help foster a culture of rigorous, practical innovation.

What we are looking for

• PhD in Computer Science, Machine Learning, Artificial Intelligence,Operations Research, or a related field.
• Extensive experience applying machine learning to solve complex real-world problems, with a track record of developing novel approaches or adapting emerging techniques in practical settings.
• Strong hands-on experience building prototypes, proof-of-concepts, and early systems that demonstrate the value of new ML and AI methods.
• Deep expertise in modern AI techniques, with strong familiarity in areas suchas agentic systems, LLMs, RAG, recommendation, optimization, explainability,and broader language-based AI techniques.
• Strong technical judgment and the ability to assess new technologiescritically, separating durable opportunities from short-term hype.
• Demonstrated ability to influence technical direction across teams throughexpertise, credibility, and collaboration.
• Strong programming ability in Python and experience working with modern MLand data tooling.
• Experience partnering closely with engineering and product teams to movepromising ideas toward scalable product capabilities.
• Excellent communication skills, with the ability to engage technical andnon-technical stakeholders and bring clarity to complex problems.
• A practical, product-minded approach to innovation, with an appreciation forenterprise software quality, maintainability, and customer