5 - 8 years
10 - 18 Lacs
Posted:2 weeks ago|
Platform:
Hybrid
Full Time
Role & responsibilities : Requirements: Strong expertise in NLP, text summarization, semantic search, and LLM APIs. Practical experience with Amazon Bedrock, OpenAI, or Hugging Face transformers. Familiar with prompt tuning and few-shot learning. Python (pandas, langchain, boto3, NumPy, etc.) Experience working with unstructured audio-to-text data (e.g., call transcripts). Key Responsibilities: Design and Development: Design, develop, and deploy LLM-based solutions for text summarization, semantic search, and other NLP tasks LLM APIs: Integrate LLM APIs from Amazon Bedrock, OpenAI, or Hugging Face transformers into existing applications Prompt Tuning and Few-Shot Learning: Implement prompt tuning and few-shot learning techniques to improve LLM performance Unstructured Audio-to-Text Data: Work with unstructured audio-to-text data, such as call transcripts, to develop accurate and efficient NLP models Python Programming: Utilize Python libraries like pandas, LangChain, boto3, and NumPy for data processing and model development Preferred candidate profile : We're seeking a highly skilled NLP Engineer with expertise in Large Language Models (LLMs) and text summarization to join our team. The ideal candidate will have hands-on experience with Amazon Bedrock, OpenAI, or Hugging Face transformers and a strong background in Python programming. This role involves working with unstructured audio-to-text data, such as call transcripts, and developing innovative solutions using LLMs.
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