Data Scientist

Key Responsibilities

• Design and build LLM guardrails for prompt injection protection, toxicity/bias detection, and hallucination/jailbreak identification.
• Build and maintain evaluation frameworks to monitor LLM safety, fairness, and compliance.
• Develop automated pipelines to process, tag, and evaluate LLM outputs using Python and SQL.
• Leverage vector databases and embeddings to detect unsafe content or model drift.
• Create internal dashboards and visualizations (Streamlit, Dash, or lightweight React/JS) for POCs and internal tools.
• Collaborate with ML engineers and product teams to integrate LLM safety components into production APIs or applications.
• Stay current with AI safety research, emerging tools (Ragas, LangChain, Guardrails.ai), and regulatory standards (EU AI Act, NIST AI RMF).

Required Qualifications

• 3 - 4.5 years of experience in data science, applied ML, or LLM-based applications.
• Strong programming skills in Python and experience writing SQL for data exploration or feature engineering.
• Solid understanding of NLP, deep learning (CNN/RNN/Transformers), and LLM architectures.
• Hands-on experience with Hugging Face, LangChain, LLM APIs (OpenAI, Anthropic), and vector stores (FAISS, Pinecone, Chroma).
• Familiarity with front-end basics (Streamlit, Dash, or simple HTML/CSS/JS) is a

  plus

  , not mandatory.
• Experience with model evaluation, red‑teaming, or safety interventions in NLP/LLM systems.
• (Preferred) Familiarity with deploying ML pipelines in production (Docker, FastAPI) and ability to thrive in a fast‑paced startup environment.