Job Summary

ML Engineer responsible for designing, developing, and deploying machine learning models for real-world business problems.
Responsibilities
- Design, develop, and deploy Machine Learning models for real-world business problems.
- Collect, clean, and pre process large datasets using Python, Pandas, and NumPy.
- Perform feature engineering to improve model accuracy and performance.
- Build and optimize classification, regression, and clustering models using Scikit-learn and other ML libraries.
- Conduct data analysis and apply statistical techniques to identify trends and insights.
- Train, validate, and evaluate machine learning models using appropriate performance metrics.
- Write productive SQL queries to extract, transform, and analyze data from databases.
- Develop and integrate REST APIs using FastAPI for model serving and application integration.
- Deploy machine learning models to cloud platforms and monitor their performance.




- Implement experiment tracking and maintain model versioning for reproducibility.
- Collaborate with data analysts, software developers, and business teams to understand project requirements.
Requirements
- Python
- SQL
- Machine Learning
- Scikit-learn
- Pandas
- NumPy
- Feature Engineering
- Model Training
- Model Evaluation
- Classification
- Regression
- Clustering
- Statistics
- Git
- Docker
- REST APIs
- FastAPI
- Cloud
- Model Deployment and Experiment Tracking

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