Experience in working with various ML libraries and packages like Scikit learn, Numpy, Pandas, Tensorflow, Matplotlib, Caffe, etc.
Deep Learning Frameworks: PyTorch, spaCy, Keras
Deep Learning Architectures: LSTM, CNN, Self-Attention and Transformers
Experience in working with Image processing, computer vision is must
Designing data science applications, Large Language Models(LLM) , Generative Pre-trained Transformers (GPT), generative AI techniques, Natural Language Processing (NLP), machine learning techniques, Python, Jupyter Notebook, common data science packages (tensorflow, scikit-learn,keras etc.,.) , LangChain, Flask, FastAPI, prompt engineering.
Programming experience in Python
Solid written and verbal communications
Excellent interpersonal and collaboration skills.
Experience working with vectored databases and graph representation of documents.
Experience with building or maintaining MLOps pipelines.
Experience in Cloud computing infrastructures like AWS Sagemaker or Azure ML for implementing ML solutions is preferred.
Exposure to Docker, Kubernetes

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