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In this Role, Your Responsibilities Will Be:
· Develop, train and deploy machine learning, deep learning AI models for a variety of business use cases such as classification, prediction, recommendation, NLP and Image Processing.
· Design and implement end-to-end ML workflows from data ingestion and preprocessing to model deployment and monitoring.
· Collect, clean, and preprocess structured and unstructured data from multiple sources using industry-standard techniques such as normalization, feature engineering, dimensionality reduction, and optimization.
· Perform exploratory data analysis (EDA) to identify patterns, correlations, and actionable insights.
· Apply advanced knowledge of machine learning algorithms including regression, classification, clustering, decision trees, ensemble methods, and neural networks.
· Use Azure ML Studio, TensorFlow, PyTorch, and other ML frameworks to implement and optimize model architectures.
· Perform hyperparameter tuning, cross-validation, and performance evaluation using industry-standard metrics to ensure model robustness and accuracy.
· Integrate models and services into business applications through RESTful APIs developed using FastAPI, Flask or Django.
· Build and maintain scalable and reusable ML components and pipelines using Azure ML Studio, Kubeflow, and MLflow.
· Enforce and integrate AI guardrails: bias mitigation, security practices, explainability, compliance with ethical and regulatory standards.
· Deploy models in production using Docker and Kubernetes, ensuring scalability, high availability, and fault tolerance.
· Utilize Azure AI services and infrastructure for development, training, inferencing, and model lifecycle management.
· Support and collaborate on the integration of large language models (LLMs), embeddings, vector databases, and RAG techniques where applicable.
· Monitor deployed models for drift, performance degradation, and data quality issues, and implement retraining workflows as needed.
· Collaborate with cross-functional teams including software engineers, product managers, business analysts, and architects to define and deliver AI-driven solutions.
· Communicate complex ML concepts, model outputs, and technical findings clearly to both technical and non-technical stakeholders.
· Stay current with the latest research, trends, and advancements in AI/ML and evaluate new tools and frameworks for potential adoption.
· Maintain comprehensive documentation of data pipelines, model architectures, training configurations, deployment steps, and experiment results.
· Drive innovation through experimentation, rapid prototyping, and the development of future-ready AI components and best practices.
· Write modular, maintainable, and production-ready code in Python with proper documentation and version control.
· Contribute to building reusable components and ML accelerators.
Qualifications:
· Strong command of Python and ML libraries (e.g., Azure ML Studio, scikit-learn, TensorFlow, PyTorch, XGBoost).
· Proficiency in Python
Preferred Qualifications:
· Hands on MLOps experience, with an appreciation of the end-to-end CI/CD process
Job Type: Full-time
Pay: ₹489,656.78 - ₹1,757,284.43 per year
Work Location: In person
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