Digital AI Engineer

Responsibilities : Analyze large datasets to extract valuable insights and identify trends.

Develop systems for real-time data processing and analytics to provide immediate insights and responses.

Develop and implement machine learning models to solve complex business problems.

Continuously refine and optimize machine learning algorithms to improve accuracy and efficiency.

Design and implement AI models to automate and enhance business processes.

Develop predictive models to forecast trends, customer behaviors, and operational outcomes.

Utilize NLP techniques to analyze and interpret unstructured data, such as customer feedback and documents.

Work with cross-functional teams to understand data requirements and deliver actionable insights.

Create and present detailed reports on findings, recommendations, and solutions.

Promotes data culture, prepare knowledge sharing and education events relating to data usage Requirements : Advanced degree in Data Science, Computer Science, Statistics, Mathematics or a related field.

Knowledge in Azure AI and ML services such as Azure AI Foundry, Azure OpenAI, Azure AI Services, Azure Machine Learning, Azure Document Intelligence.

Experience connecting Azure Data Environment with external AI LLM solutions Nice to have experience with AI services from AWS or GCP.

Strong knowledge of statistical analysis and machine learning techniques Proficiency in programming languages such as Python or R, and experience with data visualization tools Min 2 years’ work experience with AI services Good knowledge of Data Management and Governance (MDM, Data Catalog, Taxonomy, Linage) Understanding of data supply & data demand and how to make data available Preferred Qualifications : Knowledge in Azure AI and ML services such as Azure AI Foundry, Azure OpenAI, Azure AI Services, Azure Machine Learning, Azure Document Intelligence.

Experience connecting Azure Data Environment with external AI LLM solutions Familiarity with additional programming languages such as Python and R.

Knowledge of Microsoft Azure cloud platform.

Experience with AI and machine learning frameworks and libraries (e.g., TensorFlow, PyTorch).

Understanding of AI model deployment and monitoring.

Knowledge of security best practices and compliance standards in AI and cloud environments.

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