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Tier-1 brand, mid-level ML role, Bangalore location, and LLM skill demand amplify competition.
Core LLM research skills transfer broadly, but financial regulation and data-residency increase domain sensitivity.
5+ years, publications, MSc/PhD and specific LLM stack create strict screening.
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Lead applied AI research focused on open-source LLM evaluation, fine-tuning, and efficient inference to develop production-grade AI/ML capabilities.
Prototype and productionize multimodal AI models (voice, image, speech-to-text, text-to-speech) closely with engineering teams to support user-facing products.
Design rigorous evaluation methodologies and benchmarks; publish research findings and contribute to team capability enhancement and recruitment.
5+ years of applied AI/ML experience with formal training or certification in AI/ML concepts.
Advanced proficiency in Python and ML/DL frameworks such as PyTorch and Hugging Face.
Hands-on experience with evaluation, fine-tuning, and deployment of Large Language Models (LLMs).
MSc or PhD in Machine Learning, Computer Science, or related quantitative field, or equivalent applied experience.
Preference for candidates with Vice President level seniority able to lead applied research aligning with production and business needs.
Experienced in bridging research outputs into scalable engineering deployments within regulated or financial services environments.
Strong publication record or demonstrated open-source/applied research contributions in LLMs, fine-tuning, or efficient inference.