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AI Engineer

LinkedIn Children's Healthcare of Atlanta Brookhaven, GA
Not Applicable Posted March 14, 2026 Job link
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Requirements
  • Must be local and able to work hybrid
  • Must be US Citizen or Green Card Holder
  • 2 years of experience in a Machine Learning Engineering, Data Science or Data Engineering role
  • 1 year of experience in implementing machine learning algorithms in a production environment or applying software development lifecycle principles to analytics
  • Familiarity with electronic health records (e.g., Epic, Cerner), ERP (e.g., Workday), or other business systems used at Children’s.
  • Familiarity with cloud computing (Azure, AWS, Google Cloud) with focus on machine learning and data science tools (Databricks, Snowflake, Azure ML).
  • Familiarity with leveraging open-source foundation large language models to build custom domain-specific applications.
  • Working knowledge of machine learning concepts such as feature engineering, hyperparameter tuning, bias and variance tradeoff, model and data drift, and common metrics to evaluate model performance.
  • Knowledge of data structure and data modelling principles and ability to efficiently ingest and process large datasets using Python, SQL, PySpark, and Scala.
  • Knowledge of software development methodologies and architecture including API web services.
  • Skilled at writing robust, production-grade code for application in predictive analytics (e.g.,Python, R, Java, Scala).
  • Ability to reduce complexity and apply coding standards and best practices to data and machine learning pipelines, including code packaging, unit testing, data validation, containerization, automation, and CI/CD.
  • Ability to create effective technical documentation and communicate requirements to business partners and vendors.
  • Ability to work and provide coaching in agile, iterative frameworks, as well as develop in shared coding environments and collaborate with other developers using source control tools (i.e.
  • Git).
Preferred Skills
  • Experience developing software and data infrastructure to support the validation and operationalization of predictive models, including tools to support analysis, model. optimization, drift detection, model versioning, deployment and monitoring of model performance and features.
  • Experience with model training and inference in common machine learning libraries and frameworks (scikit-learn, H2O, Tensorflow, PyTorch, Datarobot).
  • Experience working with healthcare data (payer or provider) in a HIPAA regulated environment.
  • Epic certification or badges in Cogito, Cognitive Computing Platform, Chronicles and Interconnect.
  • Azure Certifications in Data Fundamentals, AI Fundamentals, Data Science or Data Engineering
  • No professional certifications required.
  • Familiarity with electronic health records (e.g., Epic, Cerner), ERP (e.g., Workday), or other business systems used at Children’s.
  • Familiarity with cloud computing (Azure, AWS, Google Cloud) with focus on machine learning and data science tools (Databricks, Snowflake, Azure ML).
  • Familiarity with leveraging open-source foundation large language models to build custom domain-specific applications.
  • Working knowledge of machine learning concepts such as feature engineering, hyperparameter tuning, bias and variance tradeoff, model and data drift, and common metrics to evaluate model performance.
  • Knowledge of data structure and data modelling principles and ability to efficiently ingest and process large datasets using Python, SQL, PySpark, and Scala.
  • Knowledge of software development methodologies and architecture including API web services.
  • Skilled at writing robust, production-grade code for application in predictive analytics (e.g.,Python, R, Java, Scala).
Education
  • (Not required) – Azure Certifications in Data Fundamentals, AI Fundamentals, Data Science or Data Engineering
  • (Not required) – Education
  • (Not required) – Bachelor’s degree in Information Systems, Data Science, Machine Learning, Computer Science, Industrial Engineering, or Analytics.
  • (Not required) – Master’s degree in Information Systems, Data Science, Machine Learning, Computer Science, Industrial Engineering, or Analytics or four years of industry experience in lieu of Master’s degree