[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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