Engineer, AI

The primary purpose of the 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 an AI Engineer, you will collaborate closely with IT Delivery Leaders, data scientists, and business stakeholders to understand and translate business needs into robust AI and data science applications. You will be responsible for the end-to-end lifecycle of AI models, including data collection, preprocessing, model development, deployment, and continuous monitoring and improvement.

Responsibilities

• Collaborate with teams to understand business requirements.
• Identify opportunities for AI solutions to solve business problems.
• Design, develop, and deploy AI models: Classic AI, Deep Learning, and Generative AI.
• Leverage machine learning frameworks such as Scikit-learn, XGBoost, TensorFlow, Keras, or PyTorch for model development.
• Determine appropriate machine learning techniques and algorithms for models and evaluate model performance using appropriate metrics and make improvements as necessary.
• Design, develop, and maintain our AIOps platform.
• Develop and maintain codebase for models using AIOps/MLOps tools (Watson Studio, GitHub) ensuring its performance, reliability, and scalability.
• Develop and maintain reports, dashboards, and visualizations to present key insights and trends effectively to stakeholders.
• Develop and maintain model data pipelines to ensure data is up-to-date and accurate.
• Work with data governance and data modeling team to source and manage model data and processes.
• Ensure data governance and security policies are adhered to.
• Document model architecture, parameters, and hyperparameters.
• Collaborate with stakeholders to integrate models into business processes and applications.

• Conduct EDA to identify relationships and trends in data.
• Identify and address data quality issues that may impact model performance.
• Use statistical techniques to identify significant variables and features.
• Develop data visualizations to communicate findings to stakeholders.
• Work with stakeholders to define success criteria for models.

• Track and report progress in Jira.
• Clearly document task requirements and completed work.
• All other duties as assigned by manager.

• University degree in Computer Science / Engineering or Mathematics.
• Cloud AI Platform Developer or Architect Certification.
• At least 3 years of experience in developing Data Science and AI applications with strong troubleshooting and problem-solving skills.
• Experience in a data science or AI-related role.
• Over 3 years of experience in developing and deploying AI and Machine Learning models, including deep learning and generative AI.
• Experience working with large datasets, data mining, and data modeling.
• Knowledge of programming languages such as Python or R.
• Experience with cloud platforms and their applications in AI/ML, such as IBM Watsonx, AWS Sagemaker, and Azure Machine Learning.
• Understanding of cloud platform services such as AWS: S3, Redshift, Glue, EMR; Azure: Blob Storage, Data Factory; IBM CP4D.
• Experience with machine learning frameworks such as Scikit-learn, XGBoost, TensorFlow, Keras, or PyTorch.
• Experience in conducting data analysis and exploratory data analysis (EDA) to identify patterns and trends.
• Background in SQL experience and data integration/processing concepts, including ETL processes.
• Experience with data processing frameworks such as Apache Spark or Hadoop.
• Experience with data visualization tools such as Tableau or Power BI.
• Experience with MLOps tools and practices, such as MLflow, Kubeflow, or Azure ML, to streamline the deployment and monitoring of AI models.
• Experience in implementing and adhering to data governance policies to ensure data quality and compliance with regulations.
• Proficiency in using version control systems like Git for collaborative development and code management.
• Experience working in Agile development environments, participating in 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.
• Enthusiastic about new technology and self-learning.
• Develops and maintains good working relationships with all members of the team.
• Develops and maintains good working relationships within Honda North America as well as all other internal and external stakeholders.
• Develops, establishes, and maintains good working relationships with Honda North America suppliers, partners, consultants, stakeholders, and other network contacts.
• Enjoys team-building approach of management and department - shares results.

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.

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