About the RoleWe are seeking a skilled LLM Specialist with 2+ years of hands-on experience working with Large Language Models, NLP pipelines, prompt engineering, and model fine-tuning. The role involves building AI-driven solutions, optimizing model performance, developing conversational agents, and integrating LLMs into real-world applications.You will collaborate with data scientists, ML engineers, and product teams to develop efficient, ethical, and scalable AI systems.Key Responsibilities1. LLM Development & Optimization- Fine-tune and optimize large language models (GPT, Llama, Mistral, Falcon, etc.). - Customize LLMs for domain-specific tasks: conversation, summarization, classification, content generation. - Work on model evaluation, prompt design, and reinforcement feedback loops.2. NLP Engineering- Build NLP pipelines for text processing, entity recognition, sentiment analysis, and retrieval augmented generation (RAG). - Implement embeddings, vector search, and semantic similarity models.3. Prompt Engineering & Model Interaction- Design effective prompts, system instructions, and multi-step workflows. - Create reusable prompt templates for different use cases. - Test, validate, and iterate prompts for accuracy and contextual alignment.4. RAG Systems & Knowledge Integration- Develop RAG pipelines using vector databases (Pinecone, Chroma, Weaviate, FAISS). - Implement document ingestion, chunking, embeddings, and retrieval workflows. - Enhance AI responses using structured + unstructured knowledge sources.5. AI Integration & Deployment- Integrate LLMs into backend systems, APIs, chatbots, and enterprise applications. - Work with frameworks like LangChain, LlamaIndex, Haystack, or custom pipelines. - Implement testing, monitoring, and performance optimization for deployed models.6. Safety, Ethics & Compliance- Apply responsible AI practices, bias detection, and output safety checks. - Ensure models comply with data privacy, PII handling, and compliance standards. - Conduct model red-teaming and robustness evaluations.7. Collaboration, Documentation & Research- Collaborate with product, engineering, and research teams to define AI features. - Create documentation, model versions, datasets, and best practices. - Stay updated with emerging LLM architectures, training techniques, and open-source tools.Required Skills & QualificationsTechnical Skills- Strong understanding of NLP, Transformers, embeddings, and LLM architectures. - Experience with Python and libraries such as Hugging Face, Transformers, LangChain, Pydantic. - Knowledge of vector databases (Pinecone, Chroma, FAISS, Weaviate). - Ability to fine-tune and deploy models on GPU/Cloud setups. - Familiar with ML frameworks: PyTorch, TensorFlow. - Experience with API-based LLMs (OpenAI, Anthropic, Google, etc.). - Understanding of evaluation metrics (BLEU, ROUGE, perplexity, accuracy).Soft Skills- Strong analytical and problem-solving ability. - Clear communication and documentation skills. - Ability to work cross-functionally and handle fast-paced environments. - Creative mindset for building AI-driven products.Preferred Qualifications- Experience with RAG, agentic workflows, or AI automation tools. - Exposure to GPU environments, model quantization, and optimization techniques. - Understanding of data engineering workflows. - Prior work on chatbots, summarization systems, or enterprise AI tools.
Job Title
LLM Specialist