Machine Learning and Operations Research Platform Engineer

Kinaxis — Canada · Posted ~5 hours ago

Mid Full-time

Skills

machine learning operations research software engineering platform development Python cloud technologies

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Summary ✨ AI‑Generated

An engineering role focused on building AI and optimization platforms, developing scalable software systems, and applying machine learning and operations research techniques to solve complex real-world problems.

Highlights

Work on advanced AI-driven platforms solving complex optimization challenges with opportunities to influence innovative technology solutions.

Description

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, we are serious about technology, we are serious about customers, and we are serious about not taking ourselves too seriously. If you are looking 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 become a global organization with over 2000 employees around the world, 6 global office and a best-in-class HQ in Ottawa, Canada. As winners of several Top Employer awards globally, we are proud to work with our customers and employees towards solving 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 powerful, 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, for our customers and for generations to come. Our cloud-based platform Maestro ensures that the products we need – everything from medicine and cars to day-to-day items like toothpaste – make it to market and into our hands when we need them with minimal ecological footprint. Our customers have terabytes of data that needs to be analyzed for the largest supply chains imaginable. Vacancy Status This is an existing job vacancy What you will do Investigate novel techniques combining class leading heuristics with optimization and MLTranslate real world Supply Chain Management use cases into mathematical modelsLead the design and implementation of mathematical models and ML systemsDefine test strategies and develop comprehensive test plansWrite unit testing, integration testing, and debugging to ensure robust and error-free softwareDesign, develop, and maintain automated test scripts for functional, regression, and performance testing using testing frameworks and toolsCollaborate closely with your agile team members and other stakeholders Technologies we use C++/Python for core developmentCommercial mathematical solversGPU ComputingMaestro’s market leading in-memory data server technologyVisual Studio, JIRA, Confluence, GitSophisticated internal testing tools to validate correctness and performanceVirtual 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 field3+ year of software development experience, track record of delivering commercial softwareWorking knowledge of C++, including object-oriented design and design patterns, unit testingExperience building and maintaining distributed services and frameworks in C++ and PythonExperience deploying and operating ML or optimization workloads in cloud or containerized environmentsA love of data structures and algorithms, and the desire to apply them in the real worldWorking knowledge of mathematical optimization and mixed-integer programming conceptsFamiliarity with commercial optimization solvers (Gurobi, Xpress, CPLEX) and their application in production systemsAbility to design, develop, and maintain automated test scripts for functional, regression, and performance testing using testing frameworks and toolsAbility to find opportunities to accelerate the SDLC through innovative application of AI or other tooling, while upholding architecture consistency, secure design, and code-quality standardsAbility to review AI-generated code rigorously for correctness, architectural fit, integration risk, and edge case support with a growth mindset and bias for experimentationFamiliarity 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 systemsExperience with MLOps, model lifecycle management, training pipelines, and inference services #Intermediate 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. People matter at Kinaxis and here are some of the perks and benefits we offer, which may vary by location and employee: Flexible vacation and Kinaxis Days (company-wide days off)Flexible work optionsPhysical and mental well-being programsRegularly scheduled virtual fitness classesMentorship programs, training, and career developmentRecognition programs and referral rewardsHackathons For more information, visit the Kinaxis website at www.kinaxis.com or the company’s blog at http://blog.kinaxis.com . Kinaxis welcomes candidates to apply to our inclusive community. We provide accommodations upon request to ensure fairness and accessibility throughout our recruitment process for all candidates, including those with specific needs or disabilities. If you require an accommodation, please reach out to us at recruitmentprograms@kinaxis.com. This contact information is for accessibility requests only and cannot be used to inquire about the status of applications. Kinaxis is committed to ensuring a fair and transparent recruitment process. We use artificial intelligence (AI) tools in the initial step of the recruitment process to compare submitted resumes against the job description to identify candidates whose education, experience, and skills most closely match the requirements of the role. After the initial screening, all subsequent decisions regarding your application, including final selection, are made by our human recruitment team. AI does not make any final hiring decisions.