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2.0 - 4.0 years

3 - 7 Lacs

Mumbai

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Roles and Responsibilities 1. Model Development & Deployment Design, develop, and optimize machine learning and deep learning models for real-world applications (classification, regression, NLP, vision, recommendation systems, etc.). Train models using large datasets and evaluate their performance using appropriate metrics. Deploy models to production using tools like Flask/FastAPI, Docker, and cloud services (AWS/GCP/Azure). 2. Data Collection & Preprocessing Collect, clean, transform, and manage structured and unstructured datasets (CSV, JSON, images, text, etc.). Perform data wrangling, feature engineering, and exploratory data analysis (EDA). 3. Algorithm Research & Implementation Research and implement AI/ML algorithms suited to business use cases. Leverage existing libraries (e.g., Scikit-learn, TensorFlow, PyTorch, Hugging Face) and fine-tune pre-trained models when applicable. 4. NLP & Computer Vision (As per domain focus) For NLP: Build and integrate models for sentiment analysis, chatbots, text summarization, translation, and entity recognition. For Vision: Apply techniques for object detection, image classification, OCR, face recognition, etc. 5. API & Application Integration Create and manage APIs to expose AI model functionalities to frontend/backend systems. Integrate models into enterprise applications, dashboards, or web platforms. 6. Model Monitoring & Maintenance Monitor model performance over time, handle concept drift, and retrain models as needed. Maintain and document ML pipelines, model versions, and deployment logs. 7. Collaboration & Agile Participation Work in cross-functional teams with data engineers, frontend/backend developers, and product owners. Participate in Agile ceremonies like standups, sprint planning, and demos.

Posted 5 days ago

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