Develop and fine-tune LLMs for classification, NLP, and generative AI use cases
Build RAG pipelines with vector databases and implement prompt engineering strategies
Conduct data preprocessing for LLM training including tokenization and embedding generation
Design custom chatbots, text generation, and document analysis solutions
Implement LLM evaluation metrics (BLEU, ROUGE, perplexity) and human feedback loops
Deploy conversational AI and content generation models in production
Technical Requirements :
2 years hands-on LLM development (GPT, BERT, T5, Llama, Claude)
Proficient in Transformers, Hugging Face, LangChain, OpenAI API
Experience with vector databases (Pinecone, Weaviate, ChromaDB) and semantic search
Strong Python, SQL, and deep learning (PyTorch, TensorFlow)
Knowledge of fine-tuning techniques (LoRA, QLoRA, PEFT) and model quantization
Understanding of prompt engineering, chain-of-thought, and few-shot learning
Familiarity with MLOps for LLMs (model versioning, A / B testing, monitoring) - GOOD TO HAVE
(ref : hirist.tech)
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Data Scientist • Gurugram
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