Primary Responsibilities
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Develop innovative AI/ML methodologies to address complex healthcare challenges using structured and unstructured data.
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Design, build, and evaluate deep learning and traditional machine learning models in distributed and cloud-based environments.
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Plan and execute experiments, perform advanced statistical analyses, and generate compelling data visualizations.
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Translate research outcomes into actionable insights and partner with business stakeholders to develop scalable AI-driven solutions.
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Collaborate with the Responsible Use of AI (RUAI) team to ensure compliance with ethical and policy standards.
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Document technical work, contribute to patents, and publish findings in top-tier conferences and journals.
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Partner with engineering teams to implement MLOps practices and develop robust, production-grade data pipelines.
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Stay current with emerging technologies, tools, and AI research literature to continuously improve solutions and methodologies.
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Adhere to company policies, procedures, and directives regarding assignments, work arrangements, and operational flexibility in a dynamic business environment.
Required Qualifications
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Bachelors degree or equivalent experience in Computer Science, Data Science, or a related quantitative discipline.
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Masters degree in a relevant field with 8+ years of professional or academic experience in AI/ML, or Ph.D. with 4+ years of experience.
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5+ years of hands-on experience in both classical machine learning and deep learning model development.
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Proficiency in deep learning frameworks such as PyTorch or TensorFlow and distributed computing environments.
Primary Responsibilities
-
Develop innovative AI/ML methodologies to address complex healthcare challenges using structured and unstructured data.
-
Design, build, and evaluate deep learning and traditional machine learning models in distributed and cloud-based environments.
-
Plan and execute experiments, perform advanced statistical analyses, and generate compelling data visualizations.
-
Translate research outcomes into actionable insights and partner with business stakeholders to develop scalable AI-driven solutions.
-
Collaborate with the Responsible Use of AI (RUAI) team to ensure compliance with ethical and policy standards.
-
Document technical work, contribute to patents, and publish findings in top-tier conferences and journals.
-
Partner with engineering teams to implement MLOps practices and develop robust, production-grade data pipelines.
-
Stay current with emerging technologies, tools, and AI research literature to continuously improve solutions and methodologies.
-
Adhere to company policies, procedures, and directives regarding assignments, work arrangements, and operational flexibility in a dynamic business environment.
Required Qualifications
-
Bachelors degree or equivalent experience in Computer Science, Data Science, or a related quantitative discipline.
-
Masters degree in a relevant field with 8+ years of professional or academic experience in AI/ML, or Ph.D. with 4+ years of experience.
-
5+ years of hands-on experience in both classical machine learning and deep learning model development.
-
Proficiency in deep learning frameworks such as PyTorch or TensorFlow and distributed computing environments.