Architect, Machine Learning (Principal Scientist)
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Key skills for this role
About the Role
Kinaxis is seeking a Machine Learning Architect to define and advance next-generation AI-driven capabilities for supply chain orchestration. The role involves applied research, product innovation, and customer impact, working across research, product, and engineering boundaries.
Key Skills for This Role
Responsibilities
- Define and advance next generation AI driven capabilities for the Kinaxis platform
- 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, develop early systems, and help guide what should move toward productization
- Identify promising techniques, develop differentiated approaches, and shape how new ideas evolve into product capabilities
- 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 and can evolve into enterprise grade software
- Mentor others across the organization and help foster a culture of rigorous, practical innovation
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 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
Full Job Posting
About Kinaxis and the Team
- Kinaxis is a global leader in modern supply chain orchestration, powering complex global supply chains.
- 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.
- The team operates at the intersection of applied research, product innovation, and customer impact.
- Kinaxis is seeking a Machine Learning Architect to help define and advance our next generation of AI driven capabilities.
What you will do
- Bring deep expertise in machine learning and applied AI, turning emerging techniques into practical solutions for real customer problems.
- 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, develop early systems, and help guide what should move toward productization.
- 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 and can evolve into enterprise grade software.
- 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.
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
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