AI Engineer Internship (Paid)

Company Description SoftwareBrio empowers businesses with software solutions driven by Artificial Intelligence. The team’s experience from organizations such as Google, Meta, and Amazon informs the design of high-impact, scalable products. The company focuses on creating innovative web applications, mobile apps, user interfaces, financial consultancy tools, and cloud-based solutions. Joining SoftwareBrio offers exposure to real-world AI applications and modern engineering practices in a dynamic, growth-oriented environment.Role Description The AI Engineer Internship (Paid) is a full-time remote role focused on supporting the design, development, and evaluation of AI-driven software solutions. Interns will assist in building and testing machine learning models, including neural networks and NLP-based systems, as well as implementing pattern recognition algorithms. Daily tasks include data preprocessing, model training and tuning, integrating models into software products, and collaborating with engineers on deployment and performance monitoring. The role also involves writing clean, maintainable code, documenting experiments and results, and participating in code reviews and sprint meetings.QualificationsStrong foundation in Computer Science and Software Development, including algorithms, data structures, and version control (e.g., Git).Knowledge of Neural Networks and Pattern Recognition, with familiarity in machine learning frameworks (e.g., PyTorch, TensorFlow).Understanding of Natural Language Processing (NLP) concepts and techniques, and experience with common NLP libraries (e.g., spaCy, Hugging Face, NLTK) is beneficial.Proficiency in at least one programming language commonly used in AI, such as Python or JavaScript, and basic experience with APIs and web services.Currently pursuing or recently completed a degree in Computer Science, Data Science, Engineering, or a related field.Ability to work independently in a remote setting, collaborate effectively in distributed teams, and communicate technical ideas clearly.Familiarity with cloud platforms (e.g., AWS, GCP, Azure), basic data engineering concepts, and interest in AI ethics and responsible AI practices is a plus.