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Tier-1 brand, metro location, mid-level ML role and broad skillset drive high competition.
Core LLM and ML engineering skills are transferable, though insurance domain experience gives modest bias.
Mandatory LLM experience, specific ML frameworks, production coding, and Kubernetes make filtering stringent.
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Design, build, and deploy large language models (LLMs) using Azure (CPU & GPU) to solve complex business challenges in P&C insurance.
Develop novel datasets and scalable data processing pipelines to support LLM pre-training, fine-tuning, and deployment workflows.
Build reusable tools and processes to streamline generative AI and LLM workflows while ensuring high-quality production code.
3+ years experience in AI/ML with strong expertise in LLM engineering including pre-training and post-training/alignment.
Proficient in Python for production code development with experience in LLM frameworks/libraries like transformers, trl, deepspeed, PyTorch.
Familiarity with distributed, high throughput, low latency architectures and container technologies (Kubernetes, Docker).
Work Experience Required: 3+ years in AI/ML; Location: Bangalore, India.
Has deep experience managing end-to-end LLM development lifecycle from dataset creation to deployment at scale.
Strong multidisciplinary problem-solving skills with ability to communicate technical solutions clearly to business stakeholders.
Experience working in complex, global teams delivering AI/ML-enabled insurance solutions and familiarity with NLP techniques for semantic extraction.