Machine Learning Intern

You will be working as a Machine Learning Intern for a duration of 6 months with a stipend of 20k per month. The internship involves a hybrid mode of working, with 3 days in the office and 2 days working from home. Your primary responsibilities will include designing and implementing cutting-edge machine learning models for complex tabular and time series data problems. Additionally, you will be tasked with developing innovative feature engineering techniques to maximize the value extracted from datasets. Researching and applying state-of-the-art algorithms in areas like automated machine learning (AutoML) and neural architecture search will also be part of your role. Furthermore, you will optimize models for performance and scalability in resource-constrained environments, contribute to the development of the company's core ML infrastructure and pipelines, and collaborate on end-to-end ML projects from problem definition to deployment and monitoring. Your involvement in strategic discussions to identify new opportunities for ML applications within the business and conducting independent research to stay updated on the latest ML advancements for tabular and time series data will be crucial. To excel in this role, you should possess a strong theoretical understanding of machine learning concepts, statistical modeling, and optimization techniques. Proven experience in developing and deploying ML models for tabular and time series data, along with advanced programming skills in Python and expertise in ML libraries and frameworks, is essential. Proficiency in working with large-scale datasets and distributed computing environments, as well as experience with modern ML techniques such as gradient boosting, neural networks, and ensemble methods, are also required. Preferred qualifications include contributions to open-source ML projects or research publications, as well as experience with cloud-native ML development and deployment. This internship offers a unique opportunity to work on cutting-edge AI and blockchain intersection projects, contributing to the company's growth and innovation in the field of machine learning.,