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Mid-level (5y) role in Bangalore increases applicant density despite specialized LLM focus.
LLM, NLP and ML skills are moderately transferable across industries, with healthcare experience as a plus.
Multiple mandatory LLM, PyTorch, LangChain, deployment, and advanced degree requirements make filtering stringent.
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Own development and optimization of Large Language Models (LLMs) including alignment, reinforcement learning, and multilingual/multimodal modeling.
Design and deploy AI infrastructure, tools, and methods to advance state-of-the-art LLM technologies with production-level ML model management ensuring high availability and low latency.
Leverage NLP, generative AI, and frameworks like PyTorch, TensorFlow, and LangChain to integrate and enhance AI functionalities across applications.
5+ years of experience specifically in NLP, Generative AI, and Large Language Models (LLMs) research.
Master’s degree in Computer Science, Computer Engineering, or a relevant technical field; Ph.D. in AI, computer science, data science, or related fields is also acceptable.
Proficient programming skills in Python and hands-on experience with ML, NLP, and DL frameworks such as PyTorch, TensorFlow, and SFT on LLM.
Familiarity with cloud platforms like AWS, GCP, or Azure; experience with model quantization or computational optimizations is a plus.
Experienced in managing end-to-end AI/ML workflows including model deployment, monitoring, and infrastructure optimization in production environments.
Demonstrated expertise integrating LLMs into diverse applications using advanced tools like LangChain to enhance natural language understanding capabilities.
Strong research and development background in NLP and generative AI aimed at pushing forward large-scale AI model technologies, preferably with healthcare domain exposure.