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About
Oversee end-to-end AI model lifecycles including training, evaluation, deployment, monitoring, and maintenance of production-quality machine learning models Design and implement CI/CD pipelines for model training, deployment, monitoring, and retraining with a focus on security, scalability, and reliability Promote responsible AI practices and ensure AI lifecycle management aligns with institutional standards and best practices
Required Qualifications
Bachelor's degree in Computer Science, Software Engineering, Data Science, Physics, Math & Statistics, or a related engineering discipline Master's degree preferred Five years of experience in machine learning engineering, data science, data engineering, and/or software engineering; three years with a Master's degree; one year with a PhD Experience developing MLOps pipelines and custom machine learning algorithms Hands-on experience in deploying and maintaining machine learning systems in production environments
Languages
- English
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