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 decisionmaking 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 endtoend lifecycle of AI models including data collection preprocessing model development deployment and continuous monitoring and improvement.

RESPONSIBILITIES

Develop implement and manage AI Models

• 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 Scikitlearn and 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 uptodate and accurate.
• Work with data governance & data modelling team to source and manage model data and processes.
• Ensure data governance and security policies are adhered to.
• Document model architecture parameters and hyperparameters.
• Documenting model architecture parameters and hyperparameters and integrating models into business processes and applications.
• Collaborate with stakeholders to integrate models into business processes and applications.

Exploratory Data Analysis

• 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.

Other Duties

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

QUALIFICATIONS

• 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 strong troubleshooting and problemsolving skills.
• Experience in a data science or AIrelated 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 Scikitlearn 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 standups and retrospectives.
• Strong problemsolving 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 selflearning.
• 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.
• Develop establish and maintain good working relationship with Honda North America suppliers partners consultants stakeholders and other network contacts.
• Enjoys team building approach of management and department shares results.