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, dedicated to optimizing supply chains and enhancing human experiences. The Operations Research Architect will drive the development of optimization and algorithmic capabilities within the platform, guiding the creation of large-scale mathematical models and high-performance algorithms to solve complex supply chain problems.
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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