Data ScientistAI EngineerAI-ML Ops
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Job Summary
Job Description:
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Design develop and deploy advanced machine learning and deep learning models to solve complex business and healthcare problems.
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Conduct exploratory data analysis (EDA) statistical analysis and hypothesis testing to uncover insights and validate business assumptions.
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Build scalable end-to-end ML solutions from data preparation and feature engineering to model deployment and monitoring.
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Develop and optimize NLP solutions using Transformer-based architectures (BERT GPT Hugging Face etc.) and representation learning techniques.
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Design and implement graph-based machine learning solutions using Graph Neural Networks (GNNs) where applicable.
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Build automate and maintain MLOps pipelines for model training validation deployment monitoring and lifecycle management.
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Deploy and manage machine learning models in cloud environments preferably on Azure using Azure Kubernetes Service (AKS) and CI/CD best practices.
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Develop robust data pipelines ETL processes and data integration workflows using modern data engineering practices.
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Work with large-scale high-dimensional datasets and optimize model performance scalability and reliability.
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Collaborate with cross-functional teams business stakeholders and global partners to translate business requirements into scalable AI and analytics solutions.
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Perform model monitoring drift detection observability and continuous improvement for production ML systems.
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Mentor junior team members and promote best practices in machine learning MLOps experimentation and software engineering.
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Stay updated with advancements in AI Machine Learning Generative AI MLOps and healthcare analytics.
