AI/ML Intern

Role Overview

SeedEdge Solutions is seeking a passionate and curious AI & Machine Learning Intern to join our growing technology team. This internship offers hands-on experience in developing AI applications, training machine learning models, working with Large Language Models (LLMs), data analysis, and building intelligent automation solutions.

Responsibilities

• Assist in developing AI and machine learning models for real-world business applications.
• Collect, clean, and preprocess datasets for model training and evaluation.
• Build and test machine learning algorithms using Python and popular ML frameworks.
• Work on Generative AI and Large Language Model (LLM) projects.
• Develop AI-powered chatbots, automation tools, and intelligent applications.
• Perform data analysis and visualization to extract actionable insights.
• Collaborate with software developers to integrate AI models into applications.
• Conduct research on emerging AI technologies and industry trends.
• Document technical work, experiments, and model performance.
• Participate in team meetings, brainstorming sessions, and project reviews.

Requirements

• Pursuing or recently completed a Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Information Technology, Electronics, or a related field.
• Basic knowledge of Artificial Intelligence and Machine Learning concepts.
• Proficiency in Python programming.
• Understanding of supervised and unsupervised learning algorithms.
• Familiarity with NumPy, Pandas, Matplotlib, and Scikit-learn.
• Basic understanding of Deep Learning frameworks such as TensorFlow or PyTorch.
• Knowledge of SQL and data preprocessing techniques.
• Strong analytical and problem-solving skills.
• Good communication and teamwork abilities.

Skills

• Python
• Scikit-learn
• PyTorch
• SQL
• Pandas

Nice to Have

• Experience with OpenAI APIs, LangChain, or LlamaIndex.
• Familiarity with Retrieval-Augmented Generation (RAG) concepts.
• Understanding of NLP and computer vision fundamentals.
• Experience with Git and GitHub.
• Knowledge of cloud platforms like AWS, Azure, or Google Cloud.
• Exposure to vector databases such as Pinecone, ChromaDB, or FAISS.

Benefits

• Hands-on experience with real-world AI and Machine Learning projects.
• Exposure to Generative AI and LLMs.
• Mentorship from experienced professionals.
• Internship Certificate and Letter of Recommendation.
• Potential opportunity for a full-time role based on performance.