Senior Data Scientist

Square One Resources is hiring for a project involving generative AI and large language models (LLMs) to solve business problems through concrete architectures and end-to-end applications.

• 6+ years of experience in Data Science/AI engineering.
• At least 4+ years of experience developing production-ready Python AI code.
• At least 2+ years of experience in production-ready LLM-related development, preferably using Retrieval-Augmented Generation (RAG).
• Strong analytical and problem-solving skills to optimize AI solutions.
• Strong knowledge and experience with Generative AI, including LLMs, chatbots, AI agents, and RAG.
• Deep understanding of LLM evaluators, validators, and guardrails.
• Hands-on experience with GenAI frameworks such as LangChain, LlamaIndex, LangGraph, or similar.
• Hands-on experience designing or operating MCP servers/clients for LLM agents.
• Strong Python skills including production-grade code, packaging, and testing for data/ML services.
• Solid understanding of ML/AI concepts, algorithms, machine learning frameworks, model efficiency metrics, lifecycle, and AI architectures.

• Lead discovery and solution design for GenAI use cases, translating business problems into architectures such as LLM decision, RAGs, fine-tuning, agents, and guardrails.
• Build end-to-end GenAI applications including data ingestion, retrieval layer, orchestration (e.g., LangChain, LlamaIndex, LangGraph), API/backend, and simple UI.
• Design and implement RAG pipelines with vector databases, hybrid search, rerankers, query transformation, and evaluation frameworks.
• Perform model selection, prompting strategies, fine-tuning (LoRA/QLoRA/SFT) for text, code, and multimodal models, including evaluation and A/B testing.
• Implement safety, compliance, and governance controls such as input/output filters, PII handling, audit logs, and human-in-the-loop review.
• Collaborate with data engineers, product owners, and full-stack developers on scalable architectures, SLAs, and integration.
• Gather technical requirements and estimate planned work.
• Mentor data scientists and engineers in GenAI patterns, code quality, and best practices; contribute to internal libraries and components.
• Stay current with GenAI landscape and perform targeted PoCs to validate new models and frameworks.