Key Responsibilities :
Derive and design use cases from structured and unstructured data.
Provide LLM expertise to solve AI problems using state-of-the-art language models and off-the-shelf LLM services such as OpenAI models.
Apply Retrieval-Augmented Generation (RAG) and relevant techniques to enhance LLM performance and capabilities.
Develop end-to-end machine learning pipelines, including model development, tuning, implementation, deployment, and MLOps.
Build and fine-tune transformer-based deep learning models.
Collaborate with business and product teams to develop and implement analytics-driven AI solutions.
Communicate findings and results to both technical and non-technical audiences.
Stay updated with the latest research and innovations in AI, ML, Deep Learning, and Generative AI.
Mandatory Skills :
Python, Scikit-learn, PyTorch, Transformers, SQL, LangChain
Model building, hyperparameter tuning, performance evaluation, and deployment
Deep Learning / LLM model fine-tuning and evaluation
Good to Have Skills :
LLMOps
Cloud experience (preferably AWS)
Experience Mix : AI / ML – 50%
Deep Learning – 25%
GenAI – Around 2 years
Computer Vision / Video Analytics – as part of DL and GenAI
Developer • Nashik, Maharashtra, India