Data Science Intern

GEN AI Engineer

Hands-on experience with at least one major machine learning framework (PyTorch, TensorFlow, Keras). • Familiarity with LLMs, prompt engineering, and fine-tuning (e.g., LoRA, QLoRA). • Exposure to RAG systems and basic knowledge of hybrid search techniques. • Understanding of model deployment and containerization (Docker). • Proficiency in Python for AI development, data preprocessing, and scripting. • Experience with generative AI tools (LangChain, Hugging Face, LlamaIndex) is a plus. • Understanding of version control systems (Git). • Awareness of AI compliance, data privacy, and responsible AI principles. Required Soft Skills: • Strong teamwork and communication abilities. • Willingness to learn new AI/ML technologies and frameworks. • Analytical mindset and attention to detail. • Openness to feedback and continuous improvement. Qualifications: • Bachelor’s degree or Master’s degree in Computer Science, Data Science, AI, or a related field. • 3–5 years of professional experience in AI/ML development, with exposure to Generative AI. • Experience delivering AI/ML projects in a collaborative setting. • Exposure to cloud-based AI/ML environments (AWS, GCP, or Azure) is a plus. mplement and fine-tune generative AI models under the guidance of senior team members. • Contribute to prompt engineering and development of AI-powered workflows. • Assist with the deployment, monitoring, and maintenance of AI models in production environments. • Collaborate with data scientists and engineers to ensure seamless integration of AI capabilities. • Perform data preprocessing, feature engineering, and API development for AI applications. • Participate in code reviews, testing, and documentation to ensure quality and reliability. • Stay updated with advancements in GenAI and share relevant learnings with the team.