Senior Large Language Model Specialist

3 days ago

Ajmer, Rajasthan, India beBeeLargeLanguageModel Full time ₹ 1,50,00,000 - ₹ 2,00,00,000
Job Opportunity

Role Overview

Key Responsibilities:

  • Design and Build LLM Guardrails: Design, develop, and implement robust guardrails for large language models to prevent prompt injection attacks, detect toxicity and bias, and identify hallucinations.
  • Evaluation Frameworks Development: Develop comprehensive evaluation frameworks to monitor the safety, fairness, and compliance of large language models.
  • Automated Pipelines Creation: Create automated data processing, tagging, and evaluation pipelines using Python and SQL to enhance the efficiency of large language model outputs.
  • Vector Database Integration: Leverage vector databases and embeddings to effectively identify and mitigate unsafe content or model drift in large language models.
  • Internal Dashboards and Visualizations: Design and implement interactive dashboards and visualizations using Streamlit, Dash, or lightweight React/JS to facilitate proof-of-concepts and internal tool development.
  • Collaboration and Integration: Collaborate closely with machine learning engineers and product teams to integrate large language model safety components into production APIs or applications.
  • Staying Current: Stay updated with the latest advancements in AI safety research, emerging tools (Ragas, LangChain, Guardrails.ai), and regulatory standards (EU AI Act, NIST AI RMF).

Required Skills and Qualifications:

  • Experience: 1-3 years of experience in data science, applied machine learning, or large language model-based applications.
  • Programming Skills: Strong programming skills in Python and experience writing SQL for data exploration and feature engineering.
  • NLP and Deep Learning Understanding: Comprehensive understanding of natural language processing, deep learning (CNN/RNN/Transformers), and large language model architectures.
  • Hands-on Experience: Hands-on experience with Hugging Face, LangChain, large language model APIs (OpenAI, Anthropic), and vector stores (FAISS, Pinecone, Chroma).
  • Front-end Basics: Familiarity with front-end basics (Streamlit, Dash, or simple HTML/CSS/JS) is a plus, not mandatory.
  • Model Evaluation and Safety: Experience with model evaluation, red-teaming, or safety interventions in natural language processing/large language model systems.
  • Deployment and Startup Environment: Familiarity with deploying machine learning pipelines in production (Docker, FastAPI) and ability to thrive in a fast-paced startup environment.

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