Data Scientist - Support Top-Tier Entrepreneurs

RAY is on a mission to enable builders & innovators to focus on work only they can do and simultaneously create exciting high-paying jobs in the global south. We envision a world in which busy work is a relic of the past. In which our brightest minds can give 110% to their mission without their lives falling apart. A world in which we give pure focus back to humanity.

We start by connecting the best and brightest founders from the US and Europe with highly skilled executive assistants from around the world. We leverage advanced AI tools and offer comprehensive training to ensure a superior experience for both our assistants and the founders they support.

A Message from Our CEO :

We are seeking a highly skilled Data Scientist with deep expertise in modern AI / ML systems, including LLMs, multimodal models, fine-tuning techniques, and advanced retrieval architectures. In this role, you will design, prototype, and deploy AI-powered solutions that leverage state-of-the-art language, vision, and agentic frameworks. You will work closely with engineering, product, and research teams across the US and Europe to bring cutting-edge AI capabilities into production environments.

Your Responsibilities :

• Design, build, and optimize LLM-powered systems using OpenAI, Anthropic, and open-source / local model families.
• Architect and implement RAG pipelines, including hybrid search, query rewriting, prompt optimization, and reranking strategies.
• Develop and maintain vector database infrastructures (Pinecone, Weaviate, Qdrant) for large-scale embedding storage and fast retrieval.
• Train, evaluate, and retrain embedding models for domain-specific semantic search and knowledge retrieval.
• Build and integrate multimodal AI solutions using OCR, CLIP, and modern vision architectures for text-image understanding.
• Apply fine-tuning techniques (LoRA / QLoRA) to adapt foundation models to organizational datasets and specialized tasks.
• Develop production-ready AI applications using Python, PyTorch, and modern orchestration frameworks.
• Implement LLM orchestration with LangChain or LlamaIndex, including evaluators, tool abstractions, memory, and RAG components.
• Establish robust evaluation frameworks to measure model performance, reduce hallucination, and ensure reliability in production.
• Build agentic workflows using AutoGen, CrewAI, or similar frameworks to power automation and multi-agent collaboration systems.
• Stay current with research trends and apply theoretical and practical insights in Generative AI to drive innovation across the organization.

What we look for :

What we offer :