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Mid-level AI/NLP role in metro with popular title and 3–6 year experience increases competition.
Specialized ML/NLP and LLM skills limit transferability, so background sensitivity is medium.
Explicit 3–6 year requirement and essential RAG, LangChain, vector DBs, and LLM expertise tighten filters.
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Design, develop, and optimize NLP and Retrieval-Augmented Generation (RAG) pipelines integrating large language models (e.g., OpenAI, Llama) for business applications.
Develop scalable, production-ready AI services and manage their performance in production environments using Python and relevant AI libraries.
Collaborate cross-functionally to integrate AI models into internal workflows and continuously improve models through automation and user feedback incorporation.
3–6 years of hands-on experience in AI, Machine Learning, and NLP.
Proficiency in Python and AI/NLP libraries such as NLTK, spaCy, Transformers, scikit-learn, and PyTorch or TensorFlow.
Experience with Langchain, RAG architecture, and vector databases like FAISS, Pinecone, or Weaviate.
Hybrid work location requirement with at least three office days per week.
Experienced in implementing and optimizing complex NLP models and Retrieval-Augmented Generation architectures in production environments.
Skilled in integrating and fine-tuning large language models and handling AI pipelines using Python and relevant libraries.
Comfortable working cross-functionally with engineering and product teams to deploy AI-driven solutions within SaaS platforms.