Architect, Machine Learning

Kinaxis Inc.

1d•Hybrid

About The Position

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.

Requirements

PhD, Master’s degree, or equivalent deep expertise 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 Haves

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.

Responsibilities

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.