NLP Systems Developer

2 weeks ago

Kota, Rajasthan, India beBeeLanguage Full time ₹ 15,00,000 - ₹ 25,00,000
Job Opportunity

We are seeking a skilled professional to design and implement natural language processing pipelines, fine-tune open-source large language models, and integrate them into real-time applications.

Key Responsibilities
  • Design and implement NLP pipelines for classification, named entity recognition, summarization, sentiment analysis, and question answering.
  • Preprocess and structure large-scale textual datasets using SpaCy, NLTK, or custom tokenizers.
  • Fine-tune and optimize open-source models (BERT, T5, GPT-style) using Hugging Face Transformers.
  • Integrate Large Language Model APIs into real-time applications and microservices.
  • Develop prompt strategies and evaluate prompt robustness; implement few/zero-shot approaches where relevant.
  • Build retrieval + generation (RAG) pipelines with vector databases (FAISS, Weaviate, Pinecone).
  • Deploy model endpoints, containerize with Docker, and collaborate on cloud deployment.
  • Monitor model performance, data drift, and user feedback; iterate based on metrics and qualitative signals.
Required Skills
  • Strong Python skills and experience with SpaCy, Transformers (Hugging Face), 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.
  • Practical knowledge of evaluation metrics (BLEU, ROUGE, perplexity, cosine similarity).
Senior Roles
  • Track record of shipping multiple production LLM/NLP systems end-to-end.
  • Strong system design skills (latency/cost tradeoffs, multi-tenant inference).
  • Mentoring/leadership experience and ownership of ML lifecycle (MLOps).
Preferred Skills
  • Experience with LangChain, LlamaIndex, PromptLayer, or similar LLMOps tooling.
  • RAG workflows and building retrieval pipelines at scale.
  • Experience in cloud deployment on AWS/GCP/Azure.
  • Contributions to open-source projects or research publications.

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