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Kinaxis
Architect, Machine Learning (Principal Scientist)Kinaxis • Toronto, Canada
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Architect, Machine Learning (Principal Scientist)

Architect, Machine Learning (Principal Scientist)

Kinaxis • Toronto, Canada
7 days ago
Job type
  • Full-time
Job description
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 locations – Remote.

The AI 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.

Machine Learning Architect 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.

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.

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.

Work With Impact Our platform directly helps companies power the world’s supply chains. We see the results of what we do out in the world every day, when we see store shelves stocked, when medications are available for our loved ones, and so much more.

Work with Fortune 500 Brands Companies across industries trust us to help them take control of their integrated business planning and digital supply chain. Some of our customers include Lockheed Martin, Unilever, P&G, ExxonMobil, Cisco and more.

Social Responsibility at Kinaxis Our Diversity, Equity, and Inclusion Committee weighs in on hiring practices, talent assessment training materials, and mandatory training on unconscious bias and inclusion fundamentals. Sustainability is key to what we do and we’re committed to a long‑term net‑zero operations strategy. We are involved in our communities and support causes where we can make the most impact.

Perks and Benefits

Flexible vacation and Kinaxis Days (company‑wide days off)

Flexible work options

Physical and mental well‑being programs

Regularly scheduled virtual fitness classes

Mentorship programs, training, and career development

Recognition programs and referral rewards

Hackathons

Accessibility / EEO Kinaxis welcomes candidates to apply to our inclusive community. We provide accommodations upon request to ensure fairness and accessibility throughout our recruitment process for all candidates, including those with specific needs or disabilities. If you require an accommodation, please reach out to us at recruitmentprograms@kinaxis.com. This contact information is for accessibility requests only and cannot be used to inquire about the status of applications.

Recruitment Process Kinaxis is committed to ensuring a fair and transparent recruitment process. We use artificial intelligence (AI) tools in the initial step of the recruitment process to compare submitted resumes against the job description to identify candidates whose education, experience, and skills most closely match the requirements of the role. After the initial screening, all subsequent decisions regarding your application, including final selection, are made by our human recruitment team. AI does not make any final hiring decisions.

For more information, visit the Kinaxis website at www.kinaxis.com or the company’s blog at http://blog.kinaxis.com.

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Architect, Machine Learning (Principal Scientist) • Toronto, Canada

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