Strong coding skills in Python or similar languages commonly used in machine learning and data science.
Hands-on experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn, or similar.
Deep understanding of machine learning algorithms, including supervised, unsupervised, and reinforcement learning techniques.
Expertise in data preprocessing, feature engineering, and handling large datasets using tools like Pandas, NumPy, or similar.
Proven experience in deploying machine-learning models into production environments, using tools like Docker, Kubernetes, or cloud services like GCP.
10.00 Years of Experience