Jobs.ca
Jobs.ca
Language
Honda Canada Inc. logo

Senior Engineer AI

Honda Canada Inc.about 17 hours ago
Markham, Ontario
Senior Level
full_time

About the role

The primary purpose of the Senior AI Engineer role is to leverage advanced data engineering and AI system architecture skills to design, develop, and deploy innovative AI solutions that address complex business challenges. This role is crucial in transforming raw data into actionable insights and intelligent applications that drive strategic decision-making and operational efficiency.

As a Senior AI Engineer, you will design, develop, and deploy enterprise-grade AI solutions spanning generative AI, automation, and traditional machine learning. You’ll collaborate with cross-functional teams, including IT delivery leaders, data scientists, and business stakeholders to translate complex business needs into impactful, scalable AI applications. You’ll own the full AI lifecycle, from data ingestion and feature engineering to model deployment, monitoring, and retraining, while ensuring all solutions meet governance standards. In this role, you’ll also mentor junior engineers and help shape the organization’s AI strategy through technical leadership and innovation.

Responsibilities

  • AI Model Lifecycle Management
  • Collaborate with cross-functional teams to understand business requirements, identify opportunities for AI solutions, and integrate models into enterprise processes and applications;
  • Lead the design, development, deployment, and maintenance of AI models using Watsonx and other enterprise AI platforms;
  • Build and maintain generative AI applications, automation pipelines, and traditional machine learning solutions;
  • Own the end-to-end AI lifecycle, including data preparation, feature engineering, model training, evaluation, deployment, monitoring, and retraining;
  • Implement scalable MLOps pipelines and production-grade AI solutions to ensure performance, reliability, and scalability;
  • Determine appropriate machine learning techniques and algorithms for models, evaluate model performance using relevant metrics, and leverage frameworks such as Scikit-learn, XGBoost, TensorFlow, Keras, or PyTorch for model development;
  • Ensure AI model governance, compliance, and ethical AI practices across the AI lifecycle;
  • Integrate AI services with enterprise applications, including use of Model Context Protocol (MCP) where required;
  • Integrate agents with tools, APIs, and knowledge bases to enable dynamic decision-making and task automation;
  • Develop and expose RESTful APIs and/or gRPC services for AI model consumption;
  • Work with data governance and data modeling teams to source and manage model data and processes;
  • Develop and maintain codebase for models using AIOps/MLOps tools (e.g., Watsonx, GitHub), ensuring performance, reliability, and scalability;
  • Develop and maintain model documentation, including architecture, parameters, hyperparameters, and lifecycle artifacts;
  • Create and maintain dashboards, reports, and visualizations to communicate model performance, business impact, and compliance outcomes;
  • Produce governance documentation to support audits, regulatory reviews, and stakeholder transparency.
  • Prompt Engineering & AI Agent Development
  • Design and implement prompt engineering strategies for large language models (LLMs) and AI agents;
  • Apply retrieval-augmented generation (RAG) techniques to enhance model grounding and response quality;
  • Align prompt workflows with solution objectives and evaluate effectiveness.
  • Exploratory Data Analysis & Feature Engineering
  • Conduct exploratory data analysis (EDA) to identify relationships, patterns, and trends in data;
  • Identify and address data quality issues that may impact model performance;
  • Use statistical techniques to select significant variables and features for model development;
  • Proficiency in vector databases (e.g.Milvus) and graph databases (e.g., Neo4j);
  • Develop data visualizations to communicate findings and insights effectively to stakeholders.
  • Stakeholder Collaboration & Technical Leadership
  • Collaborate with business, data, and engineering teams to understand requirements and translate AI capabilities into actionable business solutions;
  • Work with stakeholders to define success criteria and integrate models into business processes and applications;
  • Mentor and coach junior engineers, fostering a culture of technical excellence, innovation, and continuous learning;
  • Lead AI projects and initiatives, ensuring alignment with timelines, quality standards, and business impact;
  • Track and report progress using tools such as Jira, ensuring visibility and accountability across teams;
  • Clearly document task requirements, completed work, and model integration steps to support transparency and reproducibility;
  • Stay current with AI trends, tools, and best practices, and apply relevant innovations to enterprise AI solutions.

Qualifications

  • University Degree - Computer Science / Engineering or Mathematics;
  • Cloud AI Platform Developer or Architect Certification;
  • Watson Studio or Watson X Certification;
  • At least 8 years of experience in developing Data Science and AI applications;
  • Minimum 8 years of hands-on experience in Data Science or AI/ML roles, including generative AI, automation, and traditional machine learning;
  • Proven success in designing, developing, and deploying AI models in production environments using frameworks such as Scikit-learn, XGBoost, TensorFlow, Keras, or PyTorch;
  • Experience working with large-scale datasets, data mining, data modeling, and enterprise-grade data pipelines;
  • Strong programming skills in Python, R, or Java, with proficiency in SQL and data integration concepts including ETL;
  • Hands-on experience with enterprise AI platforms such as WatsonX, AWS SageMaker, Azure ML, or IBM Cloud Pak for Data;
  • Familiarity with cloud services including AWS (S3, Redshift, Glue, EMR), Azure (Blob Storage, Data Factory), and IBM CP4D;
  • Deep understanding of MLOps tools and practices (e.g., MLflow, Kubeflow, Azure ML) for scalable deployment, monitoring, and retraining of AI models;
  • Demonstrated ability to implement and uphold AI governance, compliance, and ethical AI standards across the model lifecycle;
  • Strong integration knowledge, including experience integrating AI services into enterprise applications and workflows; familiarity with Model Context Protocol (MCP) is required;
  • Hands-on experience integrating AI systems via MCP protocol, APIs, and microservices;
  • Skilled in conducting exploratory data analysis (EDA) and developing data visualizations using tools such as Tableau or Power BI;
  • Experience mentoring and supporting junior engineers, fostering technical growth and collaboration across teams;
  • Strategic mindset with the ability to identify and evaluate opportunities for AI-driven innovation and business impact;
  • Proficiency in using version control systems like GitHub for collaborative development and code management;
  • Strong background in Agile development environments, including sprint planning, daily stand-ups, and retrospectives;
  • Strong problem-solving skills; simplifies complex issues;
  • Effective verbal, presentation, and written communication skills;
  • Works well independently and in teams;
  • Constant learner, focused on improvement and innovation;
  • Actively shares knowledge and best practices and supports junior team members;
  • Ability to assess business needs and identify high-impact opportunities;
  • Enthusiastic about new technology and self-learning.

Please note that as of November 2nd, 2025 we will be moving to a four day in office, one day work from home model for current hybrid roles. Honda Canada Inc. is committed to providing accommodation in its recruitment processes to applicants with disabilities, upon request. The accommodation will take into account the applicant’s accessibility needs.

If you require accommodation at any time during the recruitment process, please email Human Resources at accessibility@honda.ca or call (905) 888-4331.

About Honda Canada Inc.

Motor Vehicle Manufacturing

In 1969, when Honda came to Canada, we came as a small company with a dream. We began with motorcycles and power equipment and it took a lot of work to gain the confidence and trust of Canadians. But we worked hard and over time our products earned the respect of the marketplace. And so we grew. In 1986, we built a manufacturing facility in Alliston, Ontario. In 1998, we built a second plant at that same site, and in 2008, we completed the construction of a third facility, a $154-million engine plant. In May of 2010, Honda Canada moved into our new Gold Certified LEED® (Leadership in Energy and Environmental Design) Head Office in Markham, Ontario.

Today, we source nearly $2.1 billion in goods and services from Canadian-based suppliers each year, produce approximately 400,000 vehicles annually at our manufacturing facilities and we employ more than 19,000 Canadians in manufacturing, sales offices and dealerships across the country. Simply put, Honda is a remarkable Canadian success story that will celebrate it's 55th anniversary in 2024.

Thank you Canada.

Social media posting policy: https://www.honda.ca/en/social_posting_policy

Politique de Honda Canada Inc. sur les publications dans la communauté des médias sociaux: https://www.honda.ca/fr/politique_publications_medias_sociaux