Elevate your career journey by embracing a new challenge with Kinaxis. We are experts in tech, but it’s really our people who give us passion to always seek ways to do things better. As such, we’re serious about your career growth and professional development, because People matter at Kinaxis.
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, with a brand-new HQ based in Kanata North in Ottawa. As one of Canada’s Top Employers, we are proud to work with our customers and employees towards solving some of the biggest challenges facing supply chains today.
At Kinaxis, we power the world’s supply chains to help preserve the planet’s resources and enrich the human experience. As a global leader in end-to-end supply chain management, we enable supply chain excellence for all industries, 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.
The AI team is responsible for delivering machine learning solutions in the supply and demand space for verticals such as Retail, Consumer Packaged Goods, Life Sciences, etc.
This includes problems in the space of forecasting, optimization, replenishment, recommendation, explainability, and more. The uniqueness of the team is that it performs at the intersection of technology and real business problems. You will contribute to the product that delights customers worldwide!
Kinaxis is seeking a talented and passionate Machine Learning Senior Applied Scientist to join our Machine Learning team. Your work will directly impact our enterprise-grade AI/ML software solutions, which are used by hundreds of customers worldwide to manage their supply chains.
You will operate as an expert scientist, focusing on the core challenges of model development and strategy. Your expertise will be centered on model selection, training, and comprehensive evaluation to achieve state-of-the-art results for our customers. This involves translating complex, unstructured business problems into well-defined machine learning solutions, ensuring that the resulting models and experiments are robust and reproducible. You will write high-quality and scalable code by demonstrating fluency in Python, object-oriented development, and proficiency in cloud environments.
You are expected to be thoroughly familiar with the end-to-end AI/ML solution development lifecycle. Success in this role requires collaborating closely with Platform Architects, MLOps and DevOps Engineers to integrate and deploy models into production seamlessly. This necessary partnership ensures that your advanced solutions are delivered effectively. You are a technical expert who can oversee junior ML developers, talk requirements with product managers, and proactively engage in cross-functional technical discussions, bringing your knowledge of ML to the table to ensure successful final delivery.
Advanced AI/ML Expertise: Master's in computer science or a related quantitative field with strong theoretical foundation in advanced machine learning concepts, including statistical methods for ML, Bayesian methods, generative models, stochastic processes, and model explainability.
Problem-Solving: Demonstrated ability to deconstruct vague or unstructured business goals into well-defined, actionable machine learning problems with clear success metrics.
Lead and execute POCs: Generate hypotheses, design and execute experiments, evaluate outcomes to drive go/no-go decisions, and build successful POCs into production-ready software.
Generative AI & Deep Learning Expertise: Hands-on expertise with Natural Language Processing (NLP), Deep Learning techniques, and Large Language Models (LLMs). This includes advanced model training, fine-tuning, architecture design, transformer, embedding, regularization, transfer learning, quantization, and knowledge distillation.
Cutting-Edge AI Tools: Familiarity and experience with the latest AI libraries, tools, and frameworks, such as AI Agents, RAG, prompt-engineering, and vector databases.
End-to-End ML Software Development: Proven 5+ years of experience in developing, debugging, testing, and optimizing complex machine learning solutions using Python, Pandas, Spark, etc. Strong software engineering skills.
Cloud & Distributed Systems: Demonstrated competence in working with Linux, cloud platforms (e.g., AWS, Azure, GCP), containerization tools (Docker, Kubernetes), and applying principles of distributed computing architectures.
Scientific Leadership & Mentorship: Ability to provide technical guidance, set research goals, and effectively mentor and upskill junior team members.
Technical Communication & Influence: Exceptional verbal and written communication skills, with a proven ability to effectively advocate complex technical solutions to both technical and non-technical stakeholders.
Nice to Have
Ph.D. in computer science.
Mathematical and Statistical Acumen: Solid mathematical background in linear algebra, probability, statistics, and optimization.
Solution Architecture and Delivery: Experience collaborating closely with Platform Architects and MLOps Engineers to design, implement, and optimize the production architecture and deployment pipeline for machine learning solutions.
Manufacturing & Supply Chain Domain Knowledge: Experience in the manufacturing sector, particularly with supply chain knowledge.
Research & Publication Record: Publications at relevant venues such as ACL, EMNLP, NAACL, NeurIPS, ICLR, SIGIR, or KDD.
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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, Yamaha, P&G, Honda, 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 net-zero operations strategy for the long term. We are involved in our communities and support causes where we can make the most impact.
People matter at Kinaxis and these are some of the perks and benefits we created for our team:
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. Please note that this contact information is strictly for accessibility requests and cannot be used to inquire about application statuses.
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.
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