Machine Learning Staff Applied Scientist

Description:

Kinaxis is seeking a talented and passionate Machine Learning Staff 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.

 What you will do

You will operate as a lead scientist, defining the long-term technical strategy and scientific vision for critical business domains. Your primary focus will be on solving the most ambiguous, high-impact, and multi-quarter research challenges, translating them into foundational machine learning solutions that unlock next-generation product capabilities; crucially, this role spans multiple AI/ML domains (e.g., natural language processing, deep learning, forecasting) and you will be a major contributor collaborating closely across several different product and engineering teams. You are responsible for setting up the bar, defining the organization-wide standards for model robustness, reproducibility, and rigorous evaluation methodology, while also ensuring the highest standards of software engineering excellence, leveraging your fluency in Python, object-oriented design, and deep proficiency in modern cloud environments to develop and prototype complex, scalable core ML services that deliver significant business impact.

You are expected to maintain deep expertise and familiarity with the end-to-end AI/ML solution development lifecycle and the underlying infrastructure. Success in this role requires leveraging this knowledge to provide critical architectural review and recommendation to Platform Architects, MLOps, and DevOps Engineers. You will proactively identify potential flaws or risks in deployment and design that could compromise the integrity or scalability of ML solutions, thereby influencing the production roadmap based on scientific needs. You act as a primary mentor and technical advisor for junior and senior ML developers and peers, proactively resolving organizational and technical impediments that span across multiple teams (Science, Engineering, and Product) to advance the overall technical direction of the entire ML organization.

 What we are looking for

     A dvanced 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. 
     Mathematical and Statistical Acumen : Solid mathematical background in linear algebra, probability, statistics, and optimization. 
     Problem-Solving: Exceptional 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 : Strong, 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 : Expertise and hands-on 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 8+ 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 : Expertise in Linux, cloud platforms (e.g., AWS, Azure, GCP), containerization (Docker, Kubernetes), and distributed computing architectures. 
     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. 
     Scientific Leadership & Mentorship: Drive the technical research roadmap across multiple teams or domains, serving as a principal mentor and technical advisor who systematically defines development plans, upskills senior scientists, and sets the long-term scientific standard for the organization. 
     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. 
     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. 

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:

     Flexible vacation and Kinaxis Days (company-wide day off on the last Friday of every month) 
     Flexible work options 
     Physical and mental well-being programs 
     Regularly scheduled virtual fitness classes 
     Mentorship programs and training and career development 
     Recognition programs and referral rewards 
     Hackathons