Natural Language Processing Engineer

1 day ago

Hubli, Karnataka, India beBeeNlp Full time ₹ 1,80,00,000 - ₹ 2,50,00,000

Job Description:

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  • Design and implement natural language processing pipelines for classification, named entity recognition, summarization, sentiment analysis, and question answering tasks.
  • Preprocess and structure large-scale textual datasets using specialized libraries such as SpaCy and NLTK.
  • Fine-tune and optimize transformer models using Hugging Face Transformers.
  • Integrate large language model APIs into real-time applications and microservices.
  • Develop prompt strategies and evaluate prompt robustness; implement few-shot or zero-shot approaches where relevant.
  • Build retrieval + generation (RAG) pipelines with vector databases (FAISS, Weaviate, Pinecone).
  • Deploy model endpoints (Flask/FastAPI/Streamlit), containerize with Docker, and collaborate on cloud deployment.
  • Monitor model performance, data drift, and user feedback; iterate based on metrics and qualitative signals.
  • Collaborate with product, infrastructure, and quality assurance teams to embed models safely and responsibly.
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Required Skills and Qualifications:

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  • Strong Python programming skills and experience with SpaCy, Hugging Face Transformers, and NLTK.
  • Hands-on experience fine-tuning/training transformer models (BERT, T5, GPT variants).
  • Experience integrating LLM APIs and working with prompt engineering.
  • Familiarity with embeddings, attention, tokenization, and vector similarity (cosine).
  • Experience with vector databases such as FAISS, Weaviate, or Pinecone.
  • Comfortable with Docker, Git, and REST API development (Flask/FastAPI).
  • Practical knowledge of evaluation metrics (BLEU, ROUGE, perplexity, cosine similarity).
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Benefits:

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  • Opportunity to work on cutting-edge NLP projects.
  • Collaborative team environment.
  • Professional growth and development opportunities.
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Others:

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  • Preferred qualifications include experience with LangChain, LlamaIndex, PromptLayer, or similar LLMOps tooling.
  • Experience in cloud deployment on AWS/GCP/Azure.
  • Contributions to open-source projects or research publications.

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