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Tier-1 brand and metro location increase candidate density, though niche LLM specialization reduces applicants.
Specialized LLM, multimodal and MLOps skills limit cross-industry transferability.
Requires expert LLM/MLOps experience and leadership, making shortlisting highly selective.
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Lead the ML engineering team to implement AI/ML strategy focusing on business growth, customer experience, and delivery of secure, scalable, high-performing AI software solutions.
Design, build, and operationalize multi-modal AI pipelines and multi-agent intelligence frameworks using transformer-based models and vector store integrations for advanced contextual retrieval and reasoning.
Establish and maintain end-to-end LLMOps and MLOps pipelines including continuous retraining, model governance, and Responsible AI practices ensuring fairness and transparency.
Bachelor’s or Master’s degree in Computer Science or Engineering.
Proven hands-on experience in designing, building, and deploying AI/ML and Large Language Model / Agentic solutions.
Strong programming skills in Python and SQL; experience with TensorFlow, PyTorch, or similar frameworks.
Work Experience Required: Considerable work experience with a proven track record in leading and managing complex AI/ML projects/products.
Experienced in managing teams that deliver AI/ML solutions aligned with aggressive market needs and business growth objectives.
Skilled in advanced AI techniques including transformer-based multi-modal models, hybrid statistical and deep learning methods, and generative AI.
Familiar with MLOps, LLMOps pipelines, and applying Responsible AI governance in enterprise-scale intelligence and automation environments.