Machine Learning Engineer

MACHINE LEARNING ENGINEER (PYTHON)

Ahmedabad, Gujarat | 2-4 Years Experience

Role Overview

We are seeking a skilled Python Machine Learning Engineer with approximately 2 years of hands-on experience in developing, training, evaluating, and deploying machine learning models. The ideal candidate should have a strong foundation in classical machine learning, data preprocessing, feature engineering, statistical analysis, and production-oriented Python development.

Note: MLOps, advanced time-series/signal processing, and scientific-data experience are preferred but not mandatory for this role.

Key Responsibilities

• Core Machine Learning Development: Develop and optimize machine learning models using Python (scikit-learn). Apply supervised and unsupervised learning techniques. Understand Regression, Classification, Clustering algorithms and evaluation metrics like ROC-AUC, Precision, Recall.
• Data Processing & Analysis: Leverage Strong practical experience with Pandas and NumPy to clean, transform, analyze raw datasets. Build reusable data-processing workflows for structured datasets.
• Deep Learning (Preferred): Basic understanding of neural networks (CNN, RNN, LSTM) is a plus for working on advanced model architectures.
• Model Deployment & Software Engineering: Develop clean, modular Python code. Use FastAPI/Flask to serve models via APIs. Maintain version control using Git and write unit tests.
• MLOps (Optional): Basic understanding of the ML lifecycle, experiment tracking tools like MLflow/DVC, model monitoring, and CI/CD pipelines is a plus.
• Databases: Write efficient queries in PostgreSQL or MySQL to retrieve data for ML workflows. Understand ETL concepts.

Requirements Summary

• Experience: 2 years of hands-on experience in Python and Machine Learning.
• Tech Stack: Proficiency in Python, Pandas, NumPy. Practical experience with at least one end-to-end ML project is required.
• Skill Set: Strong foundation in classical ML, feature engineering, model training/validation/hyperparameter tuning.