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Tier-1 brand and metro location increase applicants, but senior, niche multimodal/agentic requirements reduce density.
Highly specialized multimodal, LLM, and MLOps requirements mean candidates need strong ML/AI backgrounds.
Requires deep ML/LLM expertise, leadership, and specific MLOps/platform skills, making screening highly selective.
Lead ML engineering team to execute AI/ML strategy for Operational Intelligence Program enabling business growth and enhanced customer experience.
Design and productionize multi-modal AI pipelines and transformer-based models integrating diverse data types for unified intelligence.
Implement scalable backend services, LLMOps and MLOps pipelines, and ensure Responsible AI practices for model fairness, explainability, and governance.
Bachelor's or Master's degree in Computer Science or Engineering.
Proven experience leading and managing complex AI/ML projects or products with successful delivery.
Expert-level hands-on experience designing, building, and deploying conventional AI/ML and LLM/Agentic solutions.
Strong programming skills in Python and SQL; experience with TensorFlow or PyTorch is mandatory.
Experienced technology leader capable of managing teams while driving engineering best practices and innovation in AI/ML.
Depth in multi-modal transformer models, vector stores, knowledge graphs, and distributed AI systems at scale.
Strong applied knowledge of advanced statistical techniques, predictive modeling, generative AI, and cloud computing platforms (AWS preferred).