Job
Description
Role & responsibilities Develop and implement machine learning (ML) and deep learning (DL) models for real-world applications. Preprocess and analyze large datasets to extract meaningful features. Optimize AI models for performance, scalability, and deployment in production environments. Work with frameworks such as TensorFlow, PyTorch, Scikit-learn for ML/DL model development. Deploy AI models using Docker, Kubernetes, and cloud platforms (AWS, GCP, Azure). Collaborate with data scientists, MLOps engineers, and software developers to integrate AI models into production. Implement hyperparameter tuning, model optimization, and automated retraining workflows. Develop computer vision, NLP, or predictive analytics solutions as per project requirements. Ensure AI model reliability, robustness, and ethical AI compliance. Preferred candidate profile Proficiency in Python programming, including libraries like TensorFlow, Keras, PyTorch, and Scikit-learn. Strong understanding of data pre-processing, feature engineering, and model evaluation techniques. Experience in building and training machine learning/Deep Learning models . Familiarity with data manipulation libraries like Pandas, NumPy, and Matplotlib . Ability to optimize models for performance, scalability, and accuracy. Experience with version control systems like Git. Strong in Mathematical concepts like probability, Linear Algebra , P&C etc Education & Experience 1. Experience: Skilled (4-5 year) 2. Qualification: B.Tech CSE *Is as plus: UG/PG course on or similar to: Machine Learning / Deep Learning / Artificial Intelligence
