About The Role We are looking for a passionate AI Engineer Intern with a solid foundation in Python , Object-Oriented Programming (OOPs) , and an interest in Generative AI (GenAI) . The ideal candidate should also have exposure to Data Science concepts and a willingness to work on real-world AI/ML projects under the mentorship of our engineering team. Key Responsibilities Assist in designing, developing, and deploying AI-driven solutions. Work with Generative AI models for tasks like text generation, summarization etc Apply Data Science techniques for data preprocessing, exploratory analysis, and model evaluation. Collaborate with the team to write clean, maintainable, and scalable Python code. Research and experiment with the latest AI and GenAI advancements. Must-Have Skills Strong knowledge of Python programming. Good understanding of Object-Oriented Programming (OOPs) concepts. Exposure to Generative AI (GenAI) models (e.g., GPT, LLaMA, or similar). Understanding of prompt engineering, tool calling, and shot-based prompting (zero-shot, one-shot, few-shot). Basic understanding of Data Science principles (data handling, feature engineering, model building). Familiarity with libraries like NumPy, Pandas, Scikit-learn Problem-solving mindset with eagerness to learn and experiment. Good communication and collaboration skills. Nice To Have (Optional) Familiarity with libraries like PyTorch/TensorFlow. Fine-tuning LLMs. Hands-on experience with AI projects (personal, academic, or hackathons). Knowledge of software development best practices (version control, testing).

About The Role We are looking for a highly skilled Analytics/AI Engineer to bridge the gap between data engineering and data analysis. You will play a critical role in building scalable data pipelines, transforming raw data into actionable insights, and enabling data-driven decision-making across the organization. Key Responsibilities Design and implement robust, scalable data pipelines using PySpark, Python, Polars and Gen-AI. Develop data models and transformation logic to support analytics and business intelligence needs. Leverage Python and Object-Oriented Programming (OOPs) principles to build reusable and maintainable data tools and workflows. Utilize Databricks and cloud-based platforms to process and manage large datasets efficiently. Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and deliver clean, trusted data. Ensure high data quality and consistency across different systems and reports. Must-Have Skills Strong knowledge of Python programming. Good understanding of Object-Oriented Programming (OOPs) concepts. Advanced SQL skills for data manipulation and querying. Experience with PySpark, Polars for distributed and in-memory data processing. Ability to work independently in a fast-paced, agile environment. Problem-solving mindset with eagerness to learn and experiment. Good communication and collaboration skills. Nice To Have Understanding of data architecture, ETL/ELT processes, and data modelling. Knowledge on Databricks and Azure Cloud Environment. Good to have an understanding on Data Structures and Algorithms. Familiarity with best coding practices, CI/CD & version control (Git).