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AI / ML Developer - LangChain & LLM Applications

AI / ML Developer - LangChain & LLM Applications

NPG ConsultantsGurgaon
30+ days ago
Job description

We are seeking a highly skilled AI / ML Developer with expertise in Python and a strong background in developing machine learning and LLM-based AI applications. You will work on cutting-edge technologies including Retrieval Augmented Generation (RAG), Lang Chain, and Vector Databases, helping to build scalable AI systems for production use.

Key Responsibilities :

  • Design and implement ML models for various tasks, including classification, regression, clustering, NLP, and deep learning.
  • Develop and deploy AI applications with LangChain, RAG architectures, and LLMs (such as OpenAI and Huggingface).
  • Implement vector database solutions (e.g., FAISS, Pinecone, Milvus) for efficient semantic search and data retrieval.
  • Work on prompt engineering, retrieval chains, and enhance AI-driven automation for real-world applications.
  • Write clean, modular, production-ready Python code with high scalability and performance.
  • Collaborate closely with cross-functional teams, including data scientists, software engineers, and product managers.
  • Optimize AI models for inference and deployment in - cloud environments (AWS, Azure, GCP).
  • If interested, contribute to - React.js- front-end development for AI-powered applications.

Required Skills & Qualifications :

  • 7+ years of experience in AI / ML development with Python
  • Strong expertise in Machine Learning algorithms including XGBoost, SVM, Random Forests, and Logistic Regression.
  • Deep learning proficiency with Ns, RNNs, Transformers (BERT, GPT).
  • Unsupervised learning techniques (e.g., K-Means, PCA).

    • Hands-on experience with :

  • RAG architectures, LangChain, and prompt engineering
  • Vector search & semantic retrieval (e.g., BM25, DPR)
  • Python ML libraries : scikit-learn, TensorFlow / PyTorch, Huggingface Transformers
  • Familiarity with Cloud-based AI development (AWS, Azure, or GCP).

    • Nice to Have :

  • Experience with React.js for integrating AI models into web applications.
  • Exposure to MLOps tools (MLflow, Kubeflow, Airflow).
  • Knowledge of contrastive / self-supervised learning (SimCLR, CLIP).

    • (ref : hirist.tech)

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