
Language Model Engineer
2 days ago
Data Scientists play a vital role in designing and building Large Language Model (LLM) guardrails for prompt injection protection, toxicity/bias detection, and hallucination/jailbreak identification.
They are responsible for creating evaluation frameworks to monitor LLM safety, fairness, and compliance. Data Scientists must leverage vector databases and embeddings to detect unsafe content or model drift. Additionally, they must create internal dashboards and visualizations using Streamlit, Dash, or lightweight React/JS for Proof of Concepts (POCs) and internal tools.
Furthermore, Data Scientists must collaborate with ML Engineers and Product Teams to integrate LLM safety components into production APIs or applications. They must also stay current with emerging tools like Ragas, LangChain, Guardrails.ai, and regulatory standards such as the EU AI Act and NIST AI RMF.
Lastly, Data Scientists must build automated pipelines to process, tag, and evaluate LLM outputs using Python and SQL. They must also evaluate model performance, safety, and fairness.
Required Skills & Qualifications- 1-3 years of experience in data science, applied machine learning, or LLM-based applications.
- Strong programming skills in Python and experience writing SQL for data exploration or feature engineering.
- Solid understanding of Natural Language Processing (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.
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