Hi, I’m Robert Mills, a Staff AI/ML Engineer with 14 years of experience delivering GenAI, clinical NLP, and compliant ML platforms across healthcare and finance. I specialize in RAG architectures, real-time documentation automation, and HIPAA-aligned infrastructure on AWS, GCP, and Azure. I turn research prototypes into reliable, governed systems that reduce administrative burden, support better patient outcomes, and drive measurable cost savings. I collaborate with clinicians, operations leaders, and engineering teams to ensure AI is trusted, explainable, and adopted at scale. In my leadership roles, I guide cross-functional teams through the lifecycle from research to production, implementing governance playbooks, robust monitoring, and explainability features. I’ve built secure, multi-cloud platforms, moved inference to low-latency microservices, and created dashboards that demonstrate value to executives and clinicians alike, resulting in tangible adoption and measurable impact on patient care and cost efficiency.

Robert Mills

Hi, I’m Robert Mills, a Staff AI/ML Engineer with 14 years of experience delivering GenAI, clinical NLP, and compliant ML platforms across healthcare and finance. I specialize in RAG architectures, real-time documentation automation, and HIPAA-aligned infrastructure on AWS, GCP, and Azure. I turn research prototypes into reliable, governed systems that reduce administrative burden, support better patient outcomes, and drive measurable cost savings. I collaborate with clinicians, operations leaders, and engineering teams to ensure AI is trusted, explainable, and adopted at scale. In my leadership roles, I guide cross-functional teams through the lifecycle from research to production, implementing governance playbooks, robust monitoring, and explainability features. I’ve built secure, multi-cloud platforms, moved inference to low-latency microservices, and created dashboards that demonstrate value to executives and clinicians alike, resulting in tangible adoption and measurable impact on patient care and cost efficiency.

Available to hire

Hi, I’m Robert Mills, a Staff AI/ML Engineer with 14 years of experience delivering GenAI, clinical NLP, and compliant ML platforms across healthcare and finance. I specialize in RAG architectures, real-time documentation automation, and HIPAA-aligned infrastructure on AWS, GCP, and Azure. I turn research prototypes into reliable, governed systems that reduce administrative burden, support better patient outcomes, and drive measurable cost savings. I collaborate with clinicians, operations leaders, and engineering teams to ensure AI is trusted, explainable, and adopted at scale.

In my leadership roles, I guide cross-functional teams through the lifecycle from research to production, implementing governance playbooks, robust monitoring, and explainability features. I’ve built secure, multi-cloud platforms, moved inference to low-latency microservices, and created dashboards that demonstrate value to executives and clinicians alike, resulting in tangible adoption and measurable impact on patient care and cost efficiency.

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Experience Level

Expert
Expert
Expert
Expert
Expert
Expert
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Language

Afar
Advanced
Javanese
Advanced

Work Experience

Staff AI/ML Engineer - GenAI & Platform Modernization at Cognizant Technology Solutions
June 1, 2021 - October 29, 2025
Guided BlueCross NC through a major modernization from fragmented analytics pipelines to a unified, secure GenAI/ML platform aligned with clinical workflows and HIPAA compliance. Key achievements include designing a SageMaker-first multi-cloud platform with Vertex AI continuity, enabling weekly retraining on over 10M EMR + claims records; automating GPU provisioning and scale-up with Terraform and Ray; migrating inference to gRPC on EKS with Envoy, reducing end-to-end latency by approximately 45%; establishing drift and quality guardrails with Step Functions retraining; integrating CloudWatch, Prometheus, and Grafana monitoring; delivering role-aware governance dashboards using Django, MLflow, and Weights & Biases to show lineage and PHI boundaries; standardizing portable deployment artifacts to satisfy on-prem and cloud security requirements; benchmarking Inferentia vs. A100 to right-size inference; reducing cloud spend by about 32% via intelligent GPU density and auto-shutdown polici
Senior AI/ML Engineer - Clinical Analytics & NLP at Mayo Clinic
May 1, 2021 - May 1, 2021
Led CLARA – Clinical Analytics and Risk Architecture on Google Cloud – and built a unified clinical data platform on BigQuery, Healthcare API, and Dataflow; developed readmission and chronic disease risk models to guide care management; built clinical NLP to extract ICD/SNOMED codes from Epic notes; created near real-time cohort and deterioration dashboards; integrated MATLAB waveform feature engineering; embedded HIPAA compliance via CMEK encryption, VPC Service Controls, and IAM least privilege; added FHIR schema validation inside Dataflow; built forecasting models with Prophet + BigQuery features for bed-planning and staffing; conducted A/B and Bayesian studies showing reductions in 30-day readmissions; communicated results in clinical terms to drive adoption across specialties.
Machine Learning Engineer - Fraud & Credit Risk Analytics at Bank of America
April 1, 2017 - April 1, 2017
Developed fraud-detection models and real-time anomaly detection to reduce losses within regulatory guardrails; built models in Python and MATLAB tracking behavior shifts such as merchant category drift and device anomalies; deployed real-time analytics on Azure Stream Analytics and Spark; exposed risk scoring through JWT-secured APIs for low-latency decisions during live card transactions; scaled feature engineering across billions of daily transactions using Azure Data Factory + PySpark; partnered with model risk governance to ensure independent review, traceable feature sets, and 11-7 compliance; migrated CCAR stress-testing workloads from MATLAB desktops to Azure Batch; delivered Power BI dashboards to investigators, reducing alert fatigue and enabling faster threat triage and AML/SAR filings where applicable.
Python Developer - Operational Analytics Modernization at General Electric
May 1, 2014 - May 1, 2014
Built Python-based ingestion pipelines and REST APIs to gather sensor telemetry from distributed assets; created ETL flows with SQLAlchemy to combine SQL Server data with Hadoop pilots; expanded unit and integration test coverage with PyTest; introduced Jenkins-driven CI/CD and Git workflows to stabilize releases; automated nightly reporting tasks to provide leadership with current status; developed Flask dashboards surfacing downtime, anomaly spikes, and throughput signals to improve response times; optimized data parsing and transformation to reduce batch windows from hours to under 30 minutes.

Education

Master of Science in Computer Science at University of North Carolina at Chapel Hill
August 1, 2008 - May 1, 2011

Qualifications

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Industry Experience

Healthcare, Financial Services, Software & Internet, Professional Services