AI Pipeline Specialist

1 day ago

Bellary, Karnataka, India beBeeArtificialIntelligence Full time ₹ 15,00,000 - ₹ 25,00,000

Job Summary:

Design and implement cutting-edge natural language processing pipelines for classification, named entity recognition, summarization, sentiment analysis, and question-answering systems.

Collaborate with product teams to build robust and scalable models from data preprocessing to deployment and monitoring.

  • Design NLP pipelines for classification, NER, summarization, sentiment analysis, and Q&A using Python, 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.

Required Skills and Qualifications:

  • 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).

Benefits:

  • Opportunity to work on cutting-edge AI projects.
  • Collaborative and dynamic work environment.
  • Ongoing training and skill development opportunities.

Others:

  • Preferred qualifications include experience with LangChain, LlamaIndex, PromptLayer, or similar LLMOps tooling.
  • Also preferred are RAG workflows and building retrieval pipelines at scale.
  • Cloud deployment on AWS/GCP/Azure is also a plus.
  • Contributions to open-source projects or research publications are highly valued.

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