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ML Engineer

Job Description - ML Engineer


  • 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 efficient 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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