Intelligent Large Language Model Engineer

2 days ago


Mumbai, Maharashtra, India beBeeModel Full time ₹ 20,00,000 - ₹ 30,00,000
Senior Natural Language Model Engineer

  • We design and build guardrails for prompt injection protection, toxicity/bias detection, and hallucination/jailbreak identification.
  • We develop frameworks to monitor model safety, fairness, and compliance.
  • We create automated pipelines using Python and SQL to process, tag, and evaluate model outputs.
  • We leverage vector databases and embeddings to detect unsafe content or model drift.
  • We build internal dashboards and visualizations (Streamlit, Dash, or lightweight React/JS) for proofs of concept and internal tools.
  • We collaborate with machine learning engineers and product teams to integrate safety components into production APIs or applications.
  • We stay current with AI research, emerging tools (Ragas, LangChain, Guardrails.ai), and regulatory standards.

Key Responsibilities:

  • Lead the development of large language models (LLMs) to drive business outcomes.
  • Design and implement LLM-based solutions to enhance customer experience.
  • Develop and maintain a robust testing infrastructure for LLMs.
  • Collaborate with cross-functional teams to integrate LLMs into production environments.
  • Stay up-to-date with advancements in NLP, deep learning, and AI to inform LLM strategy.

Required Qualifications

  • 3+ years of experience in natural language processing, machine learning, or related field.
  • Strong programming skills in Python, 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.
  • Experience with model evaluation, red-teaming, or safety interventions in NLP systems.
  • Ability to thrive in a fast-paced startup environment.


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