Data Science Intern

We are seeking a highly motivated and talented Data Science Intern with specialized experience in Artificial Intelligence (AI) and Machine Learning (ML). As a Data Science Intern, you will have the opportunity to work on cutting-edge projects related to prompt engineering, large language model (LLM) training, and various ML capabilities such as prioritization, NLP-based classification, and clustering. This is an exciting opportunity to contribute to innovative solutions and gain hands-on experience in a dynamic and collaborative environment. Roles and Responsibilities: AI Prompt Engineering: - Collaborate with the team to design and develop effective prompts for AI models. - Experiment with different prompt strategies to enhance model performance and accuracy. - Analyze and iterate on prompt engineering techniques to optimize model outputs. LLM Training: - Assist in the training and fine-tuning of large language models. - Contribute to the development of training pipelines and workflows. - Work on improving model efficiency, scalability, and resource utilization. Machine Learning: - Prioritization: Develop and implement algorithms for prioritizing tasks, data, or processes based on machine learning techniques. - NLP-Based Classification: Build models for natural language processing-based classification tasks, ensuring high accuracy and robustness. - Clustering: Utilize machine learning algorithms for data clustering to uncover patterns and relationships in large datasets. Collaboration and Communication: - Work closely with cross-functional teams to understand project requirements and objectives. - Communicate effectively with team members and present findings in a clear and concise manner. - Collaborate with other data scientists, engineers, and stakeholders to drive project success. Research and Innovation: - Stay updated on the latest advancements in AI and ML technologies. - Contribute to the research and development of new methodologies to solve challenging problems. - Propose and implement innovative solutions to enhance model performance and efficiency. Documentation: - Document code, methodologies, and experiment results for future reference. - Create clear and comprehensive documentation for models, algorithms, and processes.