Develop, train, and deploy machine learning and deep learning models across various business domains.
Work on data preprocessing, feature engineering, and model evaluation.
Support model deployment, monitoring, and MLOps workflows.
Collaborate with product and data teams to translate data insights into deployable ML solutions.
Required Skills:
Programming: Strong proficiency in Python.
Core ML Libraries: scikit-learn, XGBoost, LightGBM
Deep Learning Frameworks: TensorFlow, PyTorch, Keras
Data Handling: NumPy, pandas
Visualization: Matplotlib, Seaborn, Plotly
Natural Language Processing (NLP): Experience in text preprocessing, embeddings, and basic transformer models.
MLOps & Deployment: Familiarity with MLflow, Docker, or cloud-based ML services (AWS SageMaker, Azure ML, GCP Vertex).
Tech Plus: Knowledge of React or Angular for model visualization and integration will be an added advantage.
Knowledge of Public cloud will be a big plus
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Data Science & AnalyticsRole Category: Data Science & Machine LearningRole: Machine Learning EngineerEmployement Type: Full time