Machine Learning/Operations Research Platform Engineer
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Key skills for this role
About the Role
Kinaxis is looking for a Machine Learning/Operations Research Platform Engineer to build infrastructure and software for ML models and optimization algorithms in supply chain applications.
Key Skills for This Role
Responsibilities
- 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
Requirements
- MSc or PhD in Computer Science, Machine Learning, Operations Research, Engineering, or related field
- 3+ year of software development experience, track record of delivering commercial software
- Working knowledge of C++, including object oriented design and design patterns, 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
- 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
- Ability to find opportunities to accelerate the SDLC through innovative application of AI or other tooling
- Ability to review AI generated code rigorously for correctness, architectural fit, integration risk, and edge case support
Full Job Posting
About Kinaxis
- Kinaxis is a global leader in modern supply chain orchestration, powering complex global supply chains.
- Our powerful, AI infused platform provides full transparency and visibility across end to end supply chains.
- We are trusted by renowned global brands to provide the agility and predictability needed to navigate today’s volatility and disruption.
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.
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+ year of software development experience, track record of delivering commercial software
- Working knowledge of C++, including object oriented design and design patterns, 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.
- Work with Fortune 500 Brands: Companies across industries trust us to help them take control of their integrated business planning and digital supply chain.
- 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.
- 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, Flexible work options, Physical and mental well being programs, Regularly scheduled virtual fitness classes, Mentorship programs, training, and
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