Architect, Machine Learning; Principal Scientist

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.

Kinaxis is a global leader in modern supply chain orchestration, powering complex global supply chains, and supporting the people who manage them. Our powerful, AI‑infused platform provides full transparency and visibility across end‑to‑end supply chains, enabling our customers to make faster, better decisions. We are trusted by renowned global brands to provide the agility and predictability needed to navigate today’s volatility and disruption.

With more than 40,000 users in over 100 countries, we are expanding our team as we continue to innovate and revolutionize how we support our customers.

Ottawa and Toronto, CA – Hybrid. Other Canadian locations – Remote.

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.

Kinaxis is seeking a Machine Learning Architect to help define and advance our next generation of AI‑driven capabilities. As part of the Product R&D organization, you will play a senior technical leadership role in applied AI, helping identify promising techniques, develop differentiated approaches, and shape how new ideas evolve into product capabilities.

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.

• 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…