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● Develop and deploy machine learning models using TensorFlow and/or PyTorch, focusing on efficient and scalable solutions.
● Implement machine learning models and preprocessing tasks with Scikit-learn to enhance performance.
● Apply supervised and unsupervised learning algorithms (e.g., SVM, Decision Trees) across various applications.
● Design, implement, and fine-tune deep learning architectures (e.g., CNNs, RNNs) to tackle complex challenges.
● Research and experiment with reinforcement learning techniques to expand capabilities.
● Contribute to the design and development of AI systems leveraging large language models (LLMs) and advanced AI techniques.
● Bachelor’s or Master’s degree in Engineering, Computer Science, or a related field.
● Minimum 3 years of Python programming experience.
● Hands-on experience with TensorFlow or PyTorch.
● Proficiency in Scikit-learn and deep learning methodologies.
● Experience with Keras, Pandas, Numpy, and Large Language Models (LLMs), such as GPT, and their applications in natural language processing and generation.
● Knowledge of data preprocessing techniques, feature engineering, and model evaluation metrics.
● Familiarity with version control systems, especially Git.
● Exposure to cloud-based AI development platforms (e.g., Google Cloud AI, AWS AI, or Azure AI).
● Familiarity with optimization techniques to improve AI model performance.
● Knowledge of deep learning architectures, including CNNs, RNNs, and transformers.