Role: LLM Scientist

(research, design, prototype advanced Generative AI systems)
Focus: Agentic AI design, RAG architecture, LLM fine-tuning, rapid Python prototyping

Key Responsibilities
Design/prototype Agentic AI / Multi-Agent systems using LangGraph, LangChain, MCP.
Fine-tune LLMs using LoRA/QLoRA; run controlled experiments (A/B tests, ablation studies).
Architect and iterate RAG pipelines (chunking, embeddings, hybrid search, reranking).
Build evaluation frameworks for GenAI (groundedness, hallucination, relevance) and implement observability (e.g., LangFuse).
Apply statistical rigor: hypothesis testing, confidence intervals, significance testing, sample-size considerations.

Required Skills
Solid Python coding; build experimental pipelines/tooling from scratch.
Deep understanding of LLMs, Transformer architecture, and GenAI fundamentals.




Hands-on experience with Agentic AI, RAG, and LLM fine-tuning.
Proficiency in LangChain, LangGraph, MCP.
Experience with vector DBs: FAISS, ChromaDB, Pinecone.
Robust grasp of ML/stats: distributions, hypothesis testing, bias-variance, regularization, overfitting/underfitting.
Model evaluation metrics: Precision, Recall, F1, ROC-AUC; classical ML (regression, classification, clustering, ensembles).

Valuable to Have
NLP techniques (BERT, embeddings, sentiment analysis).
Classical ML (XGBoost, anomaly detection).
Research background/publications in NLP/LLMs.
Experience in regulated enterprise domains.
B.Tech/M.Tech in CS/IT or related field.

📌 Llm Scientist Nagpur
🏢 Nice Software Solutions
📍 Nagpur