Job Summary

We are looking for a passionate AI Engineer with solid expertise in Python, Natural Language Processing (NLP), and Large Language Models (LLMs). Youll work on developing intelligent language-based solutions, integrating LLM APIs (like OpenAI, Cohere, Claude, Hugging Face), and building custom NLP pipelines for real-world applications.

Key Responsibilities

Model Development & NLP Engineering

- Design and build NLP pipelines for tasks like classification, NER, summarization, sentiment analysis, and Q&A.;
- Fine-tune and optimize open-source LLMs (e.g., BERT, GPT, T5) using Hugging Face Transformers.
- Preprocess and structure large-scale textual datasets using SpaCy, NLTK, or custom tokenizers.

LLM Integration & Prompt Engineering

- Integrate LLM APIs (OpenAI, Claude, Cohere, Hugging Face) into real-time applications.
- Develop and iterate on prompt strategies to maximize LLM performance and reliability.
- Collaborate with product teams to embed LLMs into chatbots, match explainers, recommendation systems, and user-facing tools.

Deployment & Continuous Improvement

- Deploy models as APIs using Flask, FastAPI, or Streamlit; containerize with Docker.




- Monitor model outputs and performance metrics; iterate based on evaluations and user feedback.
- Stay updated with the latest in GenAI, NLP benchmarks, and open-source tools.

Required Skills & Experience

- Proficient in Python and common NLP libraries (SpaCy, Transformers, NLTK, Gensim).
- Experience integrating LLM APIs and building prompt-driven applications.
- Hands-on with Hugging Face Transformers for training/fine-tuning.
- Understanding of key NLP concepts: embeddings, attention, tokenization.
- Familiarity with vector DBs like FAISS, Weaviate, or Pinecone (for RAG).
- Comfortable with Git, containerization (Docker), and basic REST API development.

Preferred Bonus Skills

- Experience with LangChain, LlamaIndex, PromptLayer, or similar LLMOps tools.
- Knowledge of RAG workflows, zero/few-shot techniques.
- Familiarity with evaluation metrics like BLEU, ROUGE, perplexity, cosine similarity.
- Exposure to AWS, GCP, or Azure for cloud deployment.
- Contributions to NLP open-source projects or research work is a plus.

📌 Ai Ml Engineer (Chennai)
🏢 Matrimony.com
📍 Chennai