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Senior ML lead with niche LLM/MLOps skills and limited brand yields moderate candidate competition.
ML/LLM and MLOps leadership skills are transferable across industries but require specialized technical depth.
Explicit 10-14 years plus many mandatory LLM, MLOps, and framework skills enforce strict shortlisting.
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Lead technical and architectural design of advanced Generative AI applications including fine-tuning and optimization of Large Language Models (LLMs).
Oversee development, orchestration, and deployment of modular AI workflows and scalable AI solutions across cloud platforms with emphasis on MLOps/LLMOps best practices.
Manage end-to-end ML pipelines, integration of multimodal LLMs and OCR, API development for model serving, and mentor AI/ML engineering teams while liaising with business stakeholders.
10-14 years total work experience in AI/ML domains including leadership roles.
Strong expertise in Python, NLP, LLM ecosystem, and agentic frameworks such as LangChain, AutoGen, CrewAI.
Hands-on experience with TensorFlow, PyTorch (especially NER and NLP tasks), and cloud platforms (AWS, Azure, GCP).
Experience implementing MLOps/CI-CD pipelines, container orchestration (Docker, Kubernetes), and production-grade ML system deployment.
Strategic leader with proven experience delivering scalable AI solutions and managing cross-functional AI/ML teams.
Expert in advanced AI architectures including modular AI workflows, LLM fine-tuning, and integration of multimodal AI technologies.
Strong operator comfortable driving end-to-end ML pipelines and cloud-native AI deployments, bridging technical and business domains effectively.