
Data Scientist
4 weeks ago
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
- 1-3 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.
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