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Metro locations, reputable analytics employer, and broad skill list increase applicant density moderately.
Deep LLM and generative AI expertise required makes cross-industry transferability limited and domain-sensitive.
Many mandatory specialized ML/LLM skills, deployment and cloud requirements increase shortlisting rigidity.
Design and implement advanced end-to-end Large Language Model (LLM) based solutions in generative AI.
Develop and maintain code libraries, tools, and frameworks supporting generative AI development with ownership throughout software lifecycle.
Collaborate with cross-functional teams to integrate solutions into core systems and contribute to roadmap alignment.
Hands-on experience with Natural Language Processing use cases like classification, topic modeling, Q&A/chatbots, summarization, content generation.
Experience with generative AI tools and platforms including SaaS LLMs (Lang chain, llama index, vector DBs, prompt engineering) and open-source frameworks (TensorFlow/PyTorch, huggingface).
Proficiency in Python and frameworks such as Docker, FastAPI, Django, Flask; familiar with Git and cloud platforms (Azure, AWS, GCP).
B.E/B.Tech/M.Tech in Computer Science or related technical degree OR equivalent; Work Experience Required: Not explicitly mentioned in the JD.
Experienced in developing and deploying advanced generative AI and NLP solutions using both SaaS and open-source LLM technologies.
Technically strong in Python-based application development, cloud environments, and managing full software development lifecycle duties.
Capable of independently driving research and implementation efforts while effectively collaborating with cross-functional teams to integrate AI solutions.