[Remote] Senior Staff Applied Scientist, AI/ML

Note: The job is a remote job and is open to candidates in USA. Kinaxis is a global leader in modern supply chain orchestration, and they are seeking a talented and passionate Sr. Staff Applied Scientist to join their Machine Learning team. In this role, you will define the technical strategy for AI/ML solutions and collaborate across teams to solve complex supply chain challenges.

Responsibilities

• 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

Skills

• 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
• Solid mathematical background in linear algebra, probability, statistics, and optimization
• Exceptional ability to deconstruct vague or unstructured business goals into well-defined, actionable machine learning problems with clear success metrics
• Generate hypotheses, design and execute experiments, evaluate outcomes to drive go/no-go decisions, and build successful POCs into production-ready software
• 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
• Expertise and hands-on experience with the latest AI libraries, tools, and frameworks, such as AI Agents, RAG, prompt-engineering, and vector databases
• Proven 8+ years of experience in developing, debugging, testing, and optimizing complex machine learning solutions using Python, Pandas, Spark, etc. Strong software engineering skills
• Expertise in Linux, cloud platforms (e.g., AWS, Azure, GCP), containerization (Docker, Kubernetes), and distributed computing architectures
• Experience collaborating closely with Platform Architects and MLOps Engineers to design, implement, and optimize the production architecture and deployment pipeline for machine learning solutions
• 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
• Exceptional verbal and written communication skills, with a proven ability to effectively advocate complex technical solutions to both technical and non-technical stakeholders
• Ph.D. in computer science
• Experience in supply chain, retail, life sciences, planning, or optimization domains
• Publications at relevant venues such as ACL, EMNLP, NAACL, NeurIPS, ICLR, SIGIR, or KDD

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

Company Overview

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