Machine Learning Internship

As an intern, your day-to-day responsibilities will include: - Researching, identifying, and understanding business requirements to identify opportunities for applying predictive modeling and machine learning techniques - Collaborating with cross-functional teams, including data scientists, software engineers, and domain experts, to define project objectives and requirements - Designing and implementing predictive modeling and machine learning solutions, including data preprocessing, feature engineering, and model selection - Developing and deploying predictive software applications into production, leveraging Python (or similar scripting languages) for efficient development - Demonstrating expertise in training and fine-tuning LLMs on diverse datasets, ensuring superior performance, and adapting models for specific applications and domains - Working with cloud-native solutions on platforms such as AWS, GCP, or Azure for scalability and flexibility - Applying a range of machine learning algorithms for different tasks, including classification (SVM, decision tree, random forest, neural network), regression (linear, polynomial, logistic, etc), and graph theory (network analytics) - Utilizing classical optimization techniques such as gradient descent and others for model optimization and parameter tuning - Utilizing deep learning techniques, including LSTM, convolutional neural networks (CNN), and recurrent neural networks (RNN), for tasks such as natural language processing, image recognition, or time series analysis - Experience with training ML models using Pytorch or tensorflow The company delivers business growth by providing AI-powered data enrichment and is currently working in stealth mode.,