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Mid-level ML/GenAI role in metros with broad skillset and recognized analytics brand increases applicant competition.
Specialized LLM, RLHF and model-finetuning expertise increases domain sensitivity despite cross-industry applicability.
Explicit 3–5 years plus mandatory LLM, finetuning, cloud and framework skills enforces strict shortlisting.
Design and implement end-to-end advanced solutions using Large Language Models (LLMs) and generative AI technologies.
Develop and maintain code libraries, tools, and frameworks supporting generative AI development, ensuring integration with core systems.
Collaborate with cross-functional teams throughout the software development lifecycle to align deliverables and maintain code quality.
3 to 5 years of work experience in data science or related fields involving NLP and generative AI.
Bachelor's or Master's degree in Computer Science or related technical discipline (B.E/B.Tech/M.Tech) or equivalent.
Hands-on experience with NLP tasks including classification, topic modeling, chatbots, document AI, and summarization.
Proficiency in Python and experience with cloud platforms (Azure, AWS, GCP); cloud certification preferred.
Experienced with Large Language Models, including SaaS LLM tools (Lang chain, llama index) and open-source frameworks (TensorFlow, PyTorch, huggingface).
Skilled in applying generative AI across multiple modalities (text, audio, image, video) with techniques like prompt engineering and fine-tuning (PEFT, RLHF).
Capable of managing end-to-end solution ownership, working collaboratively in multi-disciplinary, agile environments to deliver scalable AI applications.