Role and Responsibilities:

• Develop and implement Machine Learning and GenAI models to solve business problems and

improve decision-making.

• Design, build and deploy machine learning models in production using MLOps best practices

(CI/CD, monitoring, versioning)

• Develop and manage ML workflow using Azure ML, Azure OpenAI and Azure DevOps

• Implement AI governance frameworks, including model risk assessments, documentation and

fairness audits

• Monitor model performance and mange model lifecycle (drift detection, retraining, governance

updates)

• Document methodologies, processes, and findings to ensure transparency and reproducibility

• Work closely with data engineers and DevOps team to ensure robust data/model infrastructure

• Communicate findings and recommendations clearly to both technical and non-technical

audiences

Requirements:

• Bachelor's degree in data science, statistics, computer science, mathematics, or a related field.

• 3 to 7 years of relevant hands-on experience in data science/machine learning.

• Proficient in Python and SQL

• Familiar with major machine learning algorithms

• Experience with machine learning libraries and GenAI frameworks (e.g., Scikit-learn, PyTorch,

LangChain)

• Experience in maintaining Machine Learning production systems and MLOps.

• Understanding and experience in implementation of LLM based RAG applications will be a plus.

• Project management skills and ability to manage multiple priorities

• A drive to learn and master new technologies and techniques

• Knowledge of Databricks is a plus