LLM Development & Fine-Tuning
- Fine-tune large language models on domain-specific datasets.
- Optimize prompts and context strategies to maximize performance across diverse use cases.
- Implement and evaluate RAG (Retrieval-Augmented Generation) pipelines for knowledge-grounded AI responses.
Multi-Agent Orchestration
Build and manage multi-agent AI systems using frameworks such as LangChain, AutoGen, CrewAI, and Haystack .Design intelligent workflows where multiple AI agents collaborate, coordinate, and reason effectively.Knowledge Graphs & Reasoning
Construct and maintain knowledge graphs to enhance contextual reasoning and factual grounding of LLMs.Integrate graph-based reasoning with LLM pipelines for improved interpretability and accuracy.Evaluation & Safety
Develop robust evaluation pipelines for hallucination detection, factual alignment, safety, and ethical compliance .Define metrics and benchmarks for continuous monitoring and quality assurance of deployed models.Skills Required
Python, Deep Learning, Nlp, Tensorflow, Pytorch, data engineering