- 5+ experience in - Proficiency in at least one programming language commonly used in ML, such as Python/R - Experience with data manipulation libraries like Pandas and NumPy. -Must Have experience working with about Snowflake, Data Brics & Azure - Strong understanding and practical experience with popular ML libraries and frameworks, such as TensorFlow or PyTorch. - Familiarity with scikit-learn for traditional machine learning algorithms. - Understanding of neural network architectures, including CNNs, RNNs, and transformers. - Experience with deploying ML models to production environments. - Familiarity with containerization tools like Docker and orchestration tools like Kubernetes. - Skills in data cleaning, preprocessing, and feature engineering. - Ability to think critically about model performance, limitations, and potential improvements. - Ability to collaborate with cross-functional teams, including data scientists, software engineers, and domain experts. - Understanding on retraining the model - Understanding of reinforcement learning concepts and practical experience in applying them to real-world problems. - Participation in establishing and maintaining data governance practices to ensure data quality, privacy, and compliance. - Experience in setting up A/B tests to evaluate model performance in real-world scenarios. - Implementation of robust model monitoring systems to track performance degradation and trigger retraining as needed.