About KPMG

KPMG in Bahrain employs over 350 professionals and partners. We provide our clients with a suite of locally supported Audit, Tax and Advisory services. We recruit the best and brightest from around the world, and currently have a workforce that represents over 20 countries working across our teams. We also pride ourselves on our ability to attract, nurture and empower talent from our communities locally. We do what matters!

The Role

As a Junior GenAI Scientist, you will help develop and integrate Generative AI (GenAI) solutions using state-of-the-art frameworks and databases. This includes working with large language models (LLMs) and various retrieval and augmentation techniques like vector databases and knowledge graphs. You’ll play a key role in building AI-powered applications that rely on semantic search and context-aware reasoning, while gaining hands-on experience with cutting-edge AI tools.

Primary Responsibilities

• Assist in the development and testing of LLM-based applications using frameworks like LangChain, vector databases, and knowledge graphs to enhance information retrieval and contextual accuracy.
• Support the implementation of retrieval-augmented generation (RAG) techniques, integrating semantic search and vectorized data for more relevant and precise outputs.
• Collaborate with senior engineers to manage and optimize AI models using cloud platforms (AWS, Azure, GCP) and APIs for scalable deployment.
• Contribute to rapid prototyping, experimenting with various GenAI tools and frameworks in an agile environment.

The Individual Qualifications:

• Proficiency in Python, with a focus on AI/ML integration.
• Basic understanding of LLMOps and deploying pre-trained models into production environments.
• Interest in semantic search, vector embeddings, and retrieval-augmented generation (RAG) methods.
• Willingness to work in a dynamic, experimental environment focused on rapid learning and iteration.
• Experience: A degree in Computer Science, Software Engineering, or a related field.
• Basic exposure to Generative AI frameworks (e.g., LangChain) and technologies like vector databases (e.g., Pinecone) and knowledge graphs (e.g., Neo4j).
• Familiarity with cloud services and API-driven development is a plus.