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Machine Learning/Operations Research Platform Engineer

Kinaxis

About Kinaxis

Are you looking to join an innovative, market‑leading company where you can truly elevate your career? At Kinaxis we are serious about culture, technology, customers, and not taking ourselves too seriously. If you want to be part of an incredible growth story, then we might just be the place for you! In 1984, we started out as a team of three engineers. Today we have grown to a global organization with over 2,000 employees around the world, six global offices and a best‑in‑class headquarters in Ottawa, Canada. As winners of several Top Employer awards globally, we are proud to work with our customers and employees to solve some of the biggest challenges facing supply chains today. Kinaxis is a global leader in modern supply chain orchestration, powering complex global supply chains and supporting the people who manage them. Our AI‑infused platform provides full transparency and visibility across end‑to‑end supply chains, enabling our customers to make faster, better decisions. We are trusted by renowned global brands to provide the agility and predictability needed to navigate today’s volatility and disruption. With more than 40,000 users in over 100 countries, we are expanding our team as we continue to innovate and revolutionize how we support our customers.

Location

Ottawa or Toronto, Canada – Hybrid. All other Canadian locations – Remote.

About The Team

ML/OR Platform Engineers at Kinaxis build the infrastructure and software that allows machine‑learning models and optimization algorithms to be trained, deployed, scaled, monitored, and used in our Supply Chain applications while also contributing directly to the algorithms themselves. Each one of us plays an important part in accomplishing our work, building our culture, and making a global impact. Every day, we are empowered to work together to help our customers make fast, confident planning decisions. This is how we create a better planet – for each other, our customers and for generations to come.

What You Will Do

  • Investigate novel techniques combining class‑leading heuristics with optimization and ML
  • Translate real‑world Supply Chain Management use cases into mathematical models
  • Lead the design and implementation of mathematical models and ML systems
  • Define test strategies and develop comprehensive test plans
  • Write unit testing, integration testing, and debugging to ensure robust and error‑free software
  • Design, develop, and maintain automated test scripts for functional, regression, and performance testing using testing frameworks and tools
  • Collaborate closely with your agile team members and other stakeholders

Technologies We Use

  • C++/Python for core development
  • Commercial mathematical solvers
  • GPU Computing
  • Maestro’s market‑leading in‑memory data server technology
  • Visual Studio, JIRA, Confluence, Git
  • Sophisticated internal testing tools to validate correctness and performance
  • Virtual and cloud infrastructure for development, support and testing

What We Are Looking For

  • MSc or PhD in Computer Science, Machine Learning, Operations Research, Engineering, or related field
  • 3+ years of software development experience, track record of delivering commercial software
  • Working knowledge of C++, including object‑oriented design, design patterns, and unit testing
  • Experience building and maintaining distributed services and frameworks in C++ and Python
  • Experience deploying and operating ML or optimization workloads in cloud or containerized environments
  • A love of data structures and algorithms, and the desire to apply them in the real world
  • Working knowledge of mathematical optimization and mixed‑integer programming concepts
  • Familiarity with commercial optimization solvers (Gurobi, Xpress, CPLEX) and their application in production systems
  • Ability to design, develop, and maintain automated test scripts for functional, regression, and performance testing using testing frameworks and tools
  • 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
  • Familiarity with GPU‑accelerated computing frameworks, distributed optimization systems, or high‑performance computing environments is highly desirable

Nice‑to‑Have

  • Knowledge of Supply Chain Management (Demand Planning, MRP, S&OP, Capacity Planning)
  • Experience with GPU computing, NVIDIA CUDA, cuOpt, PDLP, or large‑scale optimization systems
  • Experience with MLOps, model lifecycle management, training pipelines, and inference services

Work With Impact

Our platform directly helps companies power the world’s supply chains. We see the results of what we do out in the world every day, when we see store shelves stocked, when medications are available for our loved ones, and so much more.

Work with Fortune 500 Brands

Companies across industries trust us to help them take control of their integrated business planning and digital supply chain. Some of our customers include Lockheed Martin, Unilever, P&G, ExxonMobil, Cisco and more.

Social Responsibility at Kinaxis

Our Diversity, Equity, and Inclusion Committee weighs in on hiring practices, talent assessment training materials, and mandatory training on unconscious bias and inclusion fundamentals. Sustainability is key to what we do and we’re committed to a long‑term net‑zero operations strategy. We are involved in our communities and support causes where we can make the most impact.

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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