Language Model Developer

2 days ago

Kannur, Kerala, India beBeeNlp Full time ₹ 2,00,00,000 - ₹ 2,50,00,000
AI Engineer Job

We are seeking an experienced AI engineer to design and implement scalable NLP pipelines, fine-tune open-source language models, and integrate them into real-time applications.

This role involves working with cross-functional teams to build classification, named entity recognition, summarization, sentiment analysis, and question-answering systems from data preprocessing to deployment and monitoring.

Responsibilities:
  • Design and implement NLP pipelines for various tasks using SpaCy, NLTK, or custom tokenizers.
  • Preprocess and structure large-scale textual datasets for training and inference.
  • Fine-tune and optimize open-source language models using Hugging Face Transformers.
  • Integrate 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 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 & 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).
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 / Nice-to-Have:
  • 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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