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Mid-level LLM role in Bangalore at a strong global brand drives high candidate competition.
Specialized LLM engineering skills are transferable, insurance domain optional, yielding medium background sensitivity.
Explicit 3+ years and mandatory LLM, PyTorch, Kubernetes, production requirements create high shortlisting strictness.
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Design, build, and deploy Large Language Models (LLMs) and AI/ML solutions to solve complex business challenges in property & casualty insurance using Azure environments.
Develop novel datasets, scalable data pipelines, and tools to enable advanced LLM capabilities and generative AI workflows at scale.
Ensure high-quality production code, manage stakeholder expectations, and adapt to shifting priorities in a global AI engineering team.
3+ years of professional experience in AI/ML engineering with specific experience in LLM pretraining, fine-tuning, and alignment techniques.
Proficient in production-grade Python programming with strong data engineering fundamentals for scalable and repeatable pipelines.
Experience with LLM frameworks/libraries (e.g., transformers, trl, deepspeed, PyTorch) and deployment on distributed, high-throughput, low-latency architectures using container technologies like Kubernetes or Docker.
Work Experience Required: 3+ years; Location Requirement: Bangalore, India
Highly experienced with end-to-end LLM lifecycle including dataset creation for pretraining and instruction tuning, prompt engineering, and deployment.
Strong interdisciplinary collaborator able to communicate complex AI/ML technical solutions clearly with business and technical stakeholders.
Skilled in building scalable AI systems with solid understanding of NLP techniques, system architecture tradeoffs, and cloud-based GPU/CPU infrastructure for enterprise use.