Design, develop, and deploy Python-based ML solutions for large-scale data analysis.
Requirements
- Strong proficiency in Python (Pandas, NumPy, Scikit-learn, FastAPI/Flask).
- Experience with machine learning workflows: data preprocessing, model training, evaluation, and deployment preferably using Microsoft stack – Azure ML, Azure Data Factory, Synapse Analytics, and related Microsoft AI/ML tools.
- Knowledge of cloud-based MLOps practices.
- Strong SQL and data modelling skills.
- Experience with deep learning frameworks (PyTorch, TensorFlow) is nice to have.
- Knowledge of containerization (Docker, Kubernetes) is nice to have.
Responsibilities
- Design, develop, and deploy Python-based ML solutions for large-scale data analysis.
- Build ETL/data pipelines to process structured and unstructured datasets.
- Perform exploratory data analysis (EDA), feature engineering, and model evaluation.
- Optimize models for scalability, performance, and accuracy.
- Mentor junior engineers and review code for quality and best practices.
Other
- Collaborate with data scientists, analysts, and business teams to translate business problems into technical solutions.
