
GenAI Intern
Training Basket · Noida, Uttar Pradesh, India
Strong hiring record · median 19 days open
All reasons
In its favour
- Still listed on the employer's own board
- Assist in developing and testing Generative AI applications using Large Language Models (LLMs).
- Work with AI models and APIs such as OpenAI, Gemini, or open-source models.
- Support prompt engineering, prompt optimization, and AI response evaluation.
- Assist in building AI-powered chatbots, virtual assistants, and automation tools.
- Work on Retrieval-Augmented Generation (RAG) applications.
- Support document processing, text generation, summarization, and semantic search projects.
- Assist in integrating LLM APIs with Python-based applications.
- Work with frameworks such as LangChain, LlamaIndex, or Hugging Face.
- Perform data preprocessing, cleaning, and preparation for AI applications.
- Test and evaluate AI model responses for accuracy, relevance, and reliability.
- Collaborate with AI/ML engineers and developers on ongoing projects.
- Maintain technical documentation and project reports.
- Stay updated with emerging trends and technologies in Generative AI.
Requirements
- Pursuing or recently completed a Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Information Technology, or a related field.
- Basic knowledge of Python programming.
- Understanding of Machine Learning, Deep Learning, and NLP fundamentals.
- Familiarity with Generative AI concepts and Large Language Models (LLMs).
- Basic understanding of prompt engineering.
- Knowledge of REST APIs and JSON.
- Familiarity with Python libraries such as Pandas, NumPy, and Scikit-learn.
- Basic knowledge of Git and GitHub.
- Good analytical, problem-solving, and communication skills.
- Willingness to learn new AI tools and technologies.
Skills
- Generative AI
- LLM
- OpenAI
- Gemini
- Prompt Engineering
- Retrieval-Augmented Generation
- Python
- LangChain
- LlamaIndex
- Hugging Face
- Machine Learning
- Deep Learning
- NLP
- JSON
- Pandas
- NumPy
- scikit-learn
- Git
- GitHub
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