[Remote] Architect, Operations Research

Note: The job is a remote job and is open to candidates in USA. Kinaxis is a global leader in end-to-end supply chain management, committed to solving complex supply chain challenges. The Operations Research Architect will drive the development of optimization and algorithmic capabilities, guiding the creation of large-scale mathematical models and high-performance algorithms to enhance supply chain solutions.

Responsibilities

• Define and drive the optimization and algorithmic strategy behind large-scale supply chain systems, shaping how advanced techniques, including mathematical optimization, heuristics, and hybrid ML/OR approaches, are designed, implemented, and evolved
• Guide the development of high-performance models that operate on massive datasets and deliver results in seconds
• Operate as a technical authority across Product R&D, setting direction for modeling approaches, solver strategies, and algorithm design
• Mentor senior engineers and researchers, elevate the organization’s approach to optimization and performance, and foster a culture grounded in analytical rigor and engineering excellence

Skills

• PhD in Operations Research, Industrial Engineering, Applied Mathematics, Computer Science, or a related field
• Extensive experience designing and delivering optimization models and algorithms in production environments
• Experience in supply chain management, logistics, or large-scale planning systems
• Deep expertise in mathematical optimization techniques, including linear programming, mixed-integer programming, heuristics, and metaheuristics
• Proven ability to formulate and solve large-scale, real-world optimization problems, particularly in supply chain or related domains
• Strong experience with commercial solvers (e.g., Gurobi, CPLEX, Xpress) and performance tuning of optimization models
• Solid understanding of algorithm design, computational complexity, and numerical performance
• Proficiency in C++ or similar high-performance programming languages, with strong software engineering fundamentals
• Familiarity with hybrid approaches combining optimization and machine learning
• Experience working with large-scale data systems and in-memory or high-performance computing environments
• Demonstrated ability to influence technical direction and lead complex decision-making across teams
• 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
• Strong background in advanced optimization techniques (stochastic optimization, robust optimization, decomposition methods)
• Familiarity with machine learning techniques applied to optimization problems
• Experience building SaaS or distributed systems that integrate optimization engines
• Exposure to cloud environments and scalable compute infrastructure
• Track record of thought leadership (publications, patents, conference speaking, or open-source contributions)

Benefits

• Flexible vacation and Kinaxis Days (company-wide day off on the third Friday of every month)
• 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

Company Overview

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