POSITION TITLE: AI Engineer
REPORTS TO: Supervisor – Data & Analytics
SCOPE OF POSITION:
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PRINCIPAL FUNCTIONAL RESPONSIBILITIES
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Develop, implement and manage AI Models
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Collaborate with teams to understand business requirements
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Identify opportunities for AI solutions to solve business problems.
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Design, Develop and Deploy AI models: Classic AI, Deep Learning and Generative AI.
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Leverage machine learning frameworks such as Scikit-learn and XGBoost, TensorFlow, Keras, or PyTorch for model development.
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Determine appropriate machine learning techniques and algorithms for models and evaluate model performance using appropriate metrics and make improvements as necessary.
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Design, develop, and maintain our AIOps platform.
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Develop and maintain codebase for models using AIOps/MLOps tools (Watson Studio, Github) ensuring its performance, reliability, and scalability.
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Develop and maintain reports, dashboards and visualizations to present key insights and trends effectively to stakeholders.
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Develop and maintain model data pipelines to ensure data is up-to-date and accurate.
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Work with data governance & data modelling team to source and manage model data and processes.
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Ensure data governance and security policies are adhered to.
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Document model architecture, parameters, and hyperparameters
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Collaborate with stakeholders to integrate models into business processes and applications.
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Exploratory Data Analysis
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Conduct EDA to identify relationships and trends in data.
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Identify and address data quality issues that may impact model performance.
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Use statistical techniques to identify significant variables and features.
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Develop data visualizations to communicate findings to stakeholders.
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Work with stakeholders to define success criteria for models.
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Communication & Reporting
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Develop clear and concise reports and presentations summarizing findings and insights.
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Deliver effective presentations to stakeholders.
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Train and support stakeholders to effectively use models and insights.
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Clearly document task requirements and completed work.
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Track and report progress work in Jira.
POSITION PROFILE AND QUALIFICATIONS
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Prior experience in a data science or AI-related role.
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3+ years of experience in developing and deploying AI and Machine Learning models including deep learning and generative AI.
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Experience working with large datasets, data mining, and data modeling.
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Strong knowledge of programming languages such as Python or R
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Proven experience with cloud platforms and their applications in AI/ML such as IBM Watsonx, AWS Sagemaker, Azure Machine Learning
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Good understanding of cloud platform services such as AWS: S3, Redshift, Glue, EMR, Azure: Blob Storage, Data Factory, IBM CP4D
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Experience with machine learning frameworks such as Scikit-learn and XGBoost, TensorFlow, Keras, or PyTorch
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Experience conducting data analysis and exploratory data analysis (EDA) to identify patterns and trends
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Strong background in SQL experience and data integration / processing concepts including ETL processes
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Experience with data processing frameworks such as Apache Spark, Hadoop or similar
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Have experience in Data Visualization tools such as Tableau or Power BI
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Strong problem-solving skills. Able to break-down complex problems into simpler ones for resolutions
RELATIONSHIP RESPONSIBILITIES
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Proven communication skills: effective verbal, presentation, and written.
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Demonstrated ability to work independently and as part of a team.
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A continuous learner who is always looking to improve and innovate.
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Proactively engage in the development and knowledge sharing, input and best practices.
ENVIRONMENTAL FACTORS
Working Conditions
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Normal
Physical Effort
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Normal
Mental Stress
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Normal