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Tier-1 brand plus Bangalore metro presence with specialized senior ML requirements yields moderate competition.
Requires deep LLM, transformer, embedding, and production MLOps expertise, limiting cross-industry portability.
Multiple explicit year cutoffs and mandatory deep ML/LLM and MLOps skills increase shortlisting strictness.
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Lead design, development, and production deployment of ML/NLP and advanced AI solutions including LLM applications, retrieval-augmented generation, and multi-agent AI systems.
Own end-to-end AI system productionization including serving, monitoring, latency optimization, drift detection, and MLOps strategy formulation.
Drive technical vision and establish standardized frameworks for scalable, reliable AI model deployment and continuous retraining.
Bachelor's Degree in Computer Science or Engineering.
Minimum 8 years of experience in traditional machine learning, advanced NLP, and model experimentation lifecycle.
At least 5 years of experience engineering and deploying production ML/AI systems with continuous integration, high-throughput serving, and monitoring.
Minimum 3 years of experience with PyTorch, Hugging Face Transformers, LangGraph, and embedding models; and 2 years in Large Language Model application development including prompt engineering and tool integration.
Experienced senior AI engineer with deep expertise in state-of-the-art NLP, LLMs, embedding models, and AI system productionization in a large-scale enterprise setting.
Demonstrated ownership in architecting and leading MLOps strategy and technical direction for reliable, cost-optimized AI model lifecycle management.
Proficient in advanced AI workflows including retrieval-augmented generation, multi-agent orchestration, and evaluation frameworks for generative AI systems.