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.

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.

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.

In 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 such as agentic systems, LLMs, RAG, recommendation, optimization, explainability, and broader language-based AI techniques.
• Strong technical judgment and the ability to assess new technologies critically, separating durable opportunities from short-term hype.
• Demonstrated ability to influence technical direction across teams through expertise, credibility, and collaboration.
• Strong programming ability in Python and experience working with modern ML and data tooling.
• Experience partnering closely with engineering and product teams to move promising ideas toward scalable product capabilities.
• Excellent communication skills, with the ability to engage technical and non-technical stakeholders and bring clarity to complex problems.
• A practical, product-minded approach to innovation, with an appreciation for enterprise software quality, maintainability, and customer impact.
• Ability to find opportunities to accelerate the SDLC through innovative application of AI or other tooling, while upholding architecture consistency, secure design, and code-quality standards.
• Ability to review AI-generated code rigorously for correctness, architectural fit, integration risk, and edge case support with a growth mindset and bias for experimentation.

Nice to Have

• Experience in supply chain, retail, life sciences, planning, or optimization domains.
• Strong mathematical foundation in areas such as probability, statistics, linear algebra, optimization, or stochastic methods.
• Experience with learning from human feedback and designing AI systems that incorporate feedback, oversight, or interaction into how they adapt and improve.
• Track record of developing intellectual property through patents, publications, inventions, or other differentiated technical contributions.
• Experience turning ambiguous customer or product problems into research directions, prototypes, and validated solution concepts.
• Familiarity with enterprise SaaS products and the considerations involved in bringing AI capabilities into production environments at scale.