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Tier-1 brand and metro location increase competition despite niche generative AI specialization and seniority.
Role requires deep LLM training, GPU cluster and inference optimization expertise, making industry transferability low.
Explicit 10+ years, mandatory LLM expertise, GPU and deployment requirements create highly strict shortlisting filters.
Architect and deliver end-to-end generative AI solutions focused on Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) workflows.
Collaborate with customers and internal teams to design tailored AI solutions, lead workshops, and support pre-sales technical activities.
Lead training, optimization, and integration of LLMs using NVIDIA hardware/software to achieve optimal performance and scalability.
Bachelor’s, Master’s, or Ph.D. in Computer Science, Artificial Intelligence, or equivalent experience.
10+ years of hands-on technical experience focused on generative AI, particularly training and deploying LLMs.
Deep expertise with state-of-the-art language models (e.g., GPT-3, BERT) and frameworks like TensorFlow, PyTorch, or Hugging Face.
Proficiency with GPU cluster architectures and optimization for LLM training and inference on GPUs.
Demonstrated success optimizing LLMs for production inference speed, memory efficiency, and resource usage.
Experience with containerization (Docker) and orchestration (Kubernetes) for scalable AI deployments.
Strong knowledge of NVIDIA GPU technologies and cluster management for distributed parallel computing workloads.