experienced engineers and data scientists, and turn your academic knowledge into practical impact. No prior professional experience is required—what matters is curiosity, problem-solving skills, and passion for AI. What You’ll Do Implement, train, and optimize ML models (supervised, unsupervised, reinforcement learning) Preprocess data, engineer features … Python (and optionally R, Java, or C++) Knowledge of ML frameworks like TensorFlow, PyTorch, or scikit-learn Eagerness to learn, curiosity, and a problem-solving mindset Nice to Have Cloud experience (AWS, GCP, Azure) Familiarity with MLOps tools (Docker, MLflow, Kubeflow) Deep learning knowledge (CNNs, RNNs, Transformers) Internship ...