Architect, Machine Learning (Principal Scientist)
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Key skills for this role
About the Role
Kinaxis is looking for a Machine Learning Architect to define and advance next-generation AI-driven capabilities for supply chain orchestration. You will provide technical leadership in applied AI, exploring emerging techniques and guiding productization.
Key Skills for This Role
Responsibilities
- Provide senior technical leadership in applied AI, helping identify promising techniques and develop differentiated approaches
- Work across research, product, and engineering boundaries to apply machine learning and Generative AI to complex supply chain problems
- Contribute through technical leadership and hands on work, using modern tools and agents to explore ideas and develop early systems
- Guide major technical decisions, identify opportunities for differentiation, and help translate new ideas into future product capabilities
- Work closely with product and engineering teams to ensure ideas are grounded in real world constraints
- Mentor others across the organization and help foster a culture of rigorous, practical innovation
- Find opportunities to accelerate the SDLC through innovative application of AI or other tooling
- Review AI generated code rigorously for correctness, architectural fit, integration risk, and edge case support
Requirements
- 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
- 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
- Strong technical judgment and the ability to assess new technologies critically
- 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
- A practical, product minded approach to innovation, with an appreciation for enterprise software quality, maintainability, and customer impact
Full Job Posting
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.
- This team operates at the intersection of applied research, product innovation, and customer impact.
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 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.
- 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 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.
Location
- Ottawa and Toronto, CA Hybrid
- Other Canadian and USA locations Remote
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