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Remote role, mid-level AI/LLM demand, popular generalist requirements increasing applicant density.
Specialized LLM and PyTorch skills transfer across industries but require specific ML experience.
Explicit 3–5 years and many mandatory LLM, tooling, and backend requirements.
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Design, build, and deploy large language model (LLM)-driven applications including document summarization, retrieval-augmented generation (RAG) QA systems, and chatbots.
Implement and optimize multi-step, multi-agent workflows using Lang Chain and Lang Graph with vector databases for RAG systems.
Collaborate with cross-functional teams to ship features to production and continuously update skills on open-source LLMs, model optimization techniques, and multi-modal AI.
3–5 years of hands-on experience in AI/ML engineering.
Proficiency in Python, PyTorch, Hugging Face Transformers, Lang Chain, Lang Graph, and experience with open-source LLMs like Ollama, Mistral, or LLaMA.
Experience with vector databases (e.g., Qdrant, Pinecone, Weaviate, FAISS) and backend technologies including FastAPI, Docker, and cloud platforms.
Location requirement: Gandhinagar; Shift: 2:30 PM to 11:30 PM IST (night shift allowance provided).
Experienced AI engineer with deep expertise in building and optimizing LLM applications specifically using Lang Chain and Lang Graph workflows.
Comfortable working in a backend-integrated environment using modern deployment tools such as FastAPI, Docker, and cloud infrastructure.
Able to stay abreast of rapidly evolving open-source LLM technologies and implement advanced model optimization and multi-modal AI techniques.