NLP Solutions Architect

6 days ago

Nagpur, Maharashtra, India beBeeArtificial Full time ₹ 25,00,000 - ₹ 30,00,000
AI Engineer

We're looking for an Artificial Intelligence Specialist to design and implement production-ready NLP pipelines, fine-tune open-source LLMs, and integrate them into real-time applications. This role involves working with product teams to build classification, NER, summarization, sentiment analysis, and QA systems.

About the Role

This position requires strong Python skills, experience with SpaCy, Transformers (Hugging Face), and NLTK. You'll also need hands-on experience fine-tuning/training Transformer models (BERT, T5, GPT variants). Additionally, you should have knowledge of embeddings, attention, tokenization, and vector similarity (cosine).

Responsibilities

  • Design and implement NLP pipelines for classification, NER, summarization, sentiment analysis, and QA.
  • 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 LLM APIs (OpenAI, Anthropic/Claude, Cohere, Hugging Face) 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 DBs (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, infra, and QA to embed models safely and responsibly.

Requirements

  • 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 DBs 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).

Bonus Points

  • 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 Experience

  • 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.

About the Company

We're a leading company in matchmaking and wedding services, providing innovative solutions to customers across India and internationally. Our mission is to dominate the $100 billion wedding services industry.

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