Large Language Model Safety Specialist

2 days ago

Coimbatore, Tamil Nadu, India beBeeData Full time ₹ 1,50,00,000 - ₹ 2,10,00,000

Key Responsibilities

  • We seek a skilled professional to design and build robust systems for protecting against prompt injection, toxicity/bias detection, and hallucination/jailbreak identification in large language models.
  • The selected candidate will be responsible for maintaining evaluation frameworks that monitor the safety, fairness, and compliance of LLMs.
  • This role requires expertise in developing automated pipelines to process, tag, and evaluate LLM outputs using Python and SQL.
  • Additionally, the ideal candidate will utilize vector databases and embeddings to detect unsafe content or model drift.
  • They will create internal dashboards and visualizations (using Streamlit, Dash, or lightweight React/JS) for proof-of-concepts and internal tools.
  • The successful applicant will collaborate with machine learning engineers and product teams to integrate LLM safety components into production APIs or applications.
  • Staying current with AI safety research, emerging tools, and regulatory standards is also essential.

Required Qualifications

  • A minimum of 1-3 years of experience in data science, applied machine learning, or large language model-based applications is required.
  • Strong programming skills in Python, as well as experience writing SQL for data exploration or feature engineering, are necessary.
  • A solid understanding of natural language processing, deep learning (CNN/RNN/Transformers), and large language model architectures is also essential.
  • Hands-on experience with Hugging Face, LangChain, LLM APIs, and vector stores (FAISS, Pinecone, Chroma) is preferred.
  • Familiarity with front-end basics (Streamlit, Dash, or simple HTML/CSS/JS) is a plus but not mandatory.
  • Experience with model evaluation, red-teaming, or safety interventions in NLP/LLM systems is highly valued.
  • (Preferred) Familiarity with deploying ML pipelines in production (Docker, FastAPI) and the ability to thrive in a fast-paced environment is desired.

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