AI Engineer

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    "description_html": "<p><strong>Company Overview</strong>:</p><p>nimble solutions is a leading provider of revenue cycle management solutions for ambulatory surgery centers (ASCs), surgical clinics, surgical hospitals, and anesthesia groups. Our tech-enabled solutions allow surgical organizations to streamline their revenue cycle processes, reduce administrative burden, and improve financial outcomes. Join over 1,100 surgical organizations that trust nimble solutions and its advisors to bring deep insights and actionable intelligence to maximize their revenue cycle.&nbsp;</p><p><br></p><p>&nbsp;<strong>Key Responsibilities</strong></p><p>? Design and implement ML models for healthcare revenue cycle applications (claim prediction, anomaly detection, outcome forecasting)</p><p>? Develop NLP solutions for healthcare document analysis, claim interpretation, and compliance classification</p><p>? Engineer production-grade ML pipelines with versioning, retraining, and A/B testing capabilities</p><p>? Implement MLOps practices including model monitoring, performance tracking, and automated retraining</p><p>? Work with large healthcare datasets, ensuring proper data preprocessing, feature engineering, and handling of missing/imbalanced data</p><p>? Collaborate with data scientists to translate research into production implementations</p><p>? Implement healthcare-compliant data pipelines that maintain HIPAA privacy and security standards</p><p>? Monitor model performance in production, diagnose drift, and implement remediation strategies</p><p>? Document model architecture, training procedures, and deployment runbooks for operational teams</p><p>? Stay current with ML research and emerging healthcare AI applications, proposing innovations to the product roadmap</p>",
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      "description": "<p>Description</p><p><strong>Company Overview</strong>:</p><p>nimble solutions is a leading provider of revenue cycle management solutions for ambulatory surgery centers (ASCs), surgical clinics, surgical hospitals, and anesthesia groups. Our tech-enabled solutions allow surgical organizations to streamline their revenue cycle processes, reduce administrative burden, and improve financial outcomes. Join over 1,100 surgical organizations that trust nimble solutions and its advisors to bring deep insights and actionable intelligence to maximize their revenue cycle. </p><p><br/></p><p> <strong>Key Responsibilities</strong></p><p>? Design and implement ML models for healthcare revenue cycle applications (claim prediction, anomaly detection, outcome forecasting)</p><p>? Develop NLP solutions for healthcare document analysis, claim interpretation, and compliance classification</p><p>? Engineer production-grade ML pipelines with versioning, retraining, and A/B testing capabilities</p><p>? Implement MLOps practices including model monitoring, performance tracking, and automated retraining</p><p>? Work with large healthcare datasets, ensuring proper data preprocessing, feature engineering, and handling of missing/imbalanced data</p><p>? Collaborate with data scientists to translate research into production implementations</p><p>? Implement healthcare-compliant data pipelines that maintain HIPAA privacy and security standards</p><p>? Monitor model performance in production, diagnose drift, and implement remediation strategies</p><p>? Document model architecture, training procedures, and deployment runbooks for operational teams</p><p>? Stay current with ML research and emerging healthcare AI applications, proposing innovations to the product roadmap</p><p>Requirements</p><p>? Healthcare domain expertise or experience applying ML in healthcare settings</p><p>? RCM industry knowledge or familiarity with healthcare claim processing</p><p>? Experience with cloud ML platforms (AWS SageMaker, Azure ML, GCP Vertex AI)</p><p>? Knowledge of responsible AI practices, model explainability, and bias mitigation</p><p>? Published research or contributions to ML open-source projects</p><p>Experience with advanced NLP models (BERT, transformers, Large Language Models </p><p>? Healthcare domain expertise or experience applying ML in healthcare settings</p><p>? RCM industry knowledge or familiarity with healthcare claim processing</p><p>? Experience with cloud ML platforms (AWS SageMaker, Azure ML, GCP Vertex AI)</p><p>? Knowledge of responsible AI practices, model explainability, and bias mitigation</p><p>? Published research or contributions to ML open-source projects</p><p>Experience with advanced NLP models (BERT, transformers, Large Language Models </p><p>? Healthcare domain expertise or experience applying ML in healthcare settings</p><p>? RCM industry knowledge or familiarity with healthcare claim processing</p><p>? Experience with cloud ML platforms (AWS SageMaker, Azure ML, GCP Vertex AI)</p><p>? Knowledge of responsible AI practices, model explainability, and bias mitigation</p><p>? Published research or contributions to ML open-source projects</p><p>Experience with advanced NLP models (BERT, transformers, Large Language Models </p>",
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    "requirements_html": "<p>? Healthcare domain expertise or experience applying ML in healthcare settings</p><p>? RCM industry knowledge or familiarity with healthcare claim processing</p><p>? Experience with cloud ML platforms (AWS SageMaker, Azure ML, GCP Vertex AI)</p><p>? Knowledge of responsible AI practices, model explainability, and bias mitigation</p><p>? Published research or contributions to ML open-source projects</p><p>Experience with advanced NLP models (BERT, transformers, Large Language Models&nbsp;</p><p>? Healthcare domain expertise or experience applying ML in healthcare settings</p><p>? RCM industry knowledge or familiarity with healthcare claim processing</p><p>? Experience with cloud ML platforms (AWS SageMaker, Azure ML, GCP Vertex AI)</p><p>? Knowledge of responsible AI practices, model explainability, and bias mitigation</p><p>? Published research or contributions to ML open-source projects</p><p>Experience with advanced NLP models (BERT, transformers, Large Language Models&nbsp;</p><p>? Healthcare domain expertise or experience applying ML in healthcare settings</p><p>? RCM industry knowledge or familiarity with healthcare claim processing</p><p>? Experience with cloud ML platforms (AWS SageMaker, Azure ML, GCP Vertex AI)</p><p>? Knowledge of responsible AI practices, model explainability, and bias mitigation</p><p>? Published research or contributions to ML open-source projects</p><p>Experience with advanced NLP models (BERT, transformers, Large Language Models&nbsp;</p>",
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