Generative AI Engineer - RAG / Machine Learning

We are looking for a Generative AI Expert with strong knowledge in Retrieval- Augmented Generation (RAG) and machine learning / deep learning (ML / DL). You will work on building intelligent systems that combine large language models (LLMs) with document retrieval to generate accurate and context-aware responses.

Your role will involve developing and improving ML / DL models, fine-tuning LLMs, and integrating retrieval systems using vector databases. Youll collaborate with cross- functional teams to build real-world AI solutions that make use of both unstructured data (like PDFs and web pages) and structured sources.

Key Responsibilities :

• Design, build, and optimize RAG pipelines for document-level and multi-turn QA systems.
• Fine-tune or prompt-tune foundation models (LLMs) for domain-specific tasks.
• Develop and deploy ML / DL models to support NLP / NLU tasks like summarization, classification, and retrieval scoring.
• Integrate vector databases, semantic search tools, and embedding models for high-performance document retrieval.
• Work with unstructured and semi-structured data sources (PDFs, HTML, JSON, SQL, etc.).
• Collaborate with data engineers, ML engineers, and product teams to build end- to-end generative AI solutions.
• Monitor performance, latency, and relevance metrics; iterate on retrieval and generation models.
• Implement prompt engineering strategies and hybrid approaches (rule-based + neural) to enhance model reliability.
• Contribute to research and innovation in applied generative AI, and stay up-to- date with the latest in LLM, RAG, and MLOps ecosystems.

Key Skills Required :

(ref : hirist.tech)