AIML Software Engineer, AI for Science
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The role
Design and implement scalable cloud-native infrastructure and software to support large-scale AI models and agentic systems across the software development lifecycle.
Develop and maintain sophisticated machine learning and deep learning pipelines that process massive datasets with optimal resource utilization.
Build cloud architectures that enable seamless deployment, scaling, and efficient compute for AI/ML workloads.
Deliver robust, tested, high-performance code in an agile environment while applying software engineering best practices, including CI/CD, testing, and containerization.
Collaborate with AI/ML engineers, data scientists, and domain experts to design fit-for-purpose data pipelines and infrastructure for cutting-edge scientific projects.
Work across locations and cloud environments, focusing on performance, scalability, and cost efficiency when working with biomedical data.
Develop and maintain sophisticated machine learning and deep learning pipelines that process massive datasets with optimal resource utilization.
Build cloud architectures that enable seamless deployment, scaling, and efficient compute for AI/ML workloads.
Deliver robust, tested, high-performance code in an agile environment while applying software engineering best practices, including CI/CD, testing, and containerization.
Collaborate with AI/ML engineers, data scientists, and domain experts to design fit-for-purpose data pipelines and infrastructure for cutting-edge scientific projects.
Work across locations and cloud environments, focusing on performance, scalability, and cost efficiency when working with biomedical data.
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