Senior AI/ML Engineer (LLM, RAG, MLOps)

Corey McCall

Senior Machine Learning / Artificial Intelligence Engineer

***************@*******.*** 321-***-**** Cocoa, FL SUMMARY

Senior Machine Learning / Artificial Intelligence Engineer with 12+ years of experience designing, building, and deploying scalable AI/ML systems, intelligent automation platforms, and production-grade software solutions across healthcare technology, SaaS, analytics, and enterprise software environments. Strong expertise in Python, PyTorch, TensorFlow, Machine Learning, Deep Learning, Natural Language Processing, LLMs, MLOps, AWS, MongoDB, and cloud-based application development. Experienced developing NLP pipelines, retrieval systems, document processing platforms, predictive analytics solutions, and scalable backend services for operational and customer-facing applications. Proven ability to translate ambiguous business requirements into practical engineering solutions, collaborate with leadership and distributed teams, and deliver reliable AI systems in fast-moving environments

EDUCATION

Bachelor’s Degree in Computer Science

University of Florida Gainesville, FL 2009 - 2013 SKILLS

• Artificial Intelligence and Machine Learning

Machine Learning, Artificial Intelligence, Deep Learning, LLMs, NLP, RAG, Document Understanding, Information Extraction, Predictive Modeling, Classification, Regression, Clustering, Anomaly Detection, Feature Engineering, Model Evaluation, Benchmarking, Statistical Modeling, OCR-Assisted Document Processing

• Machine Learning Frameworks and Libraries

Python, PyTorch, TensorFlow, scikit-learn, Pandas, NumPy, LangChain, MLflow

• Cloud Platforms, Automation, and MLOps

AWS, Docker, Kubernetes, CI/CD Pipelines, MLOps, Model Deployment, Model Monitoring, Cloud Infrastructure, Workflow Automation, Playwright, Scalable ML Services

• Data Engineering and Databases

ETL Pipelines, SQL, PostgreSQL, MySQL, MongoDB, PySpark, Apache Spark, Large-Scale Data Processing, Data Validation, Data Ingestion Pipelines

• Software Engineering and Web Technologies

FastAPI, REST APIs, Backend Development, API Integration, Node.js, React, Scalable Backend Services, System Integration

EXPERIENCE

Senior Machine Learning / Artificial Intelligence Engineer Cotiviti South Jordan, UT Jan 2025 – Present

• Designed and Deployed scalable AI/ML systems using Python, PyTorch, FastAPI, Docker, and AWS infrastructure supporting healthcare automation and enterprise operational systems.

• Built and maintained LLM-based applications using OpenAI APIs, LangChain, and retrieval- augmented workflows for internal knowledge management and document search initiatives.

• Developed scalable NLP pipelines for extracting structured information from healthcare documents, operational records, and semi-structured datasets.

• Implemented OCR-assisted document processing workflows to improve extraction reliability from scanned files and PDF-based records.

• Designed automated model evaluation, benchmarking, and validation workflows supporting continuous testing and operational monitoring of machine learning services.

• Developed feedback-driven review workflows incorporating user corrections and operational input to support ongoing model refinement and output consistency.

• Built backend inference services and scalable APIs using FastAPI, REST APIs, and deployment workflows supporting real-time AI applications.

• Supported model deployment, infrastructure configuration, and operational maintenance processes for cloud-based ML systems.

• Supported browser automation and workflow tooling using Playwright, internal automation services, and API-driven integrations.

• Collaborated with leadership, engineering teams, and product stakeholders to convert evolving requirements into structured technical implementation plans.

• Contributed to scalable MLOps practices using MLflow, Kubernetes, automated deployment workflows, and monitoring processes.

Senior Data Scientist

Sharecare Atlanta, GA Jul 2017 – Dec 2024

• Developed production-oriented Machine Learning and Deep Learning solutions using Python, TensorFlow, scikit-learn, and SQL to support healthcare analytics and operational automation initiatives.

• Built scalable data ingestion, preprocessing, feature engineering, and model evaluation workflows supporting enterprise predictive analytics systems.

• Designed and maintained end-to-end ML pipelines covering data preparation, model training, deployment, validation, and operational monitoring processes.

• Developed NLP systems for document classification, information extraction, retrieval workflows, and reporting processes involving unstructured healthcare datasets.

• Applied classification, regression, clustering, anomaly detection, and statistical modeling techniques to support operational decision-making and workflow optimization initiatives.

• Built reusable backend services using Python, Node.js, and REST APIs supporting integration of machine learning outputs into internal applications and reporting systems.

• Collaborated with frontend engineering teams supporting internal operational tools and reporting applications built with React.

• Worked with MongoDB, PostgreSQL, and large-scale data processing workflows supporting healthcare analytics initiatives.

• Supported cloud deployment and infrastructure workflows using Docker, Kubernetes, and automated CI/CD processes across distributed engineering environments.

• Assisted with implementation of scalable MLOps practices involving deployment automation, model validation, monitoring workflows, and operational support processes.

• Contributed to internal retrieval and LLM-assisted tooling initiatives supporting platform modernization efforts during later-stage product development cycles. Data Scientist

eviCore healthcare Melbourne, FL May 2014 – Jun 2017

• Developed scalable data processing and analytical workflows using Python, SQL, and enterprise reporting technologies supporting healthcare operational analytics initiatives.

• Built recurring ETL pipelines, data transformation workflows, and automated reporting systems supporting business intelligence and analytics processes.

• Applied statistical analysis, exploratory data analysis, and foundational predictive modeling techniques to operational and customer-related datasets.

• Developed reusable SQL queries, aggregation workflows, joins, and validation routines supporting recurring analytical delivery and reporting automation processes.

• Worked with structured datasets across PostgreSQL, MySQL, and cloud-based storage systems to improve reporting reliability and data accessibility.

• Assisted with backend integration workflows involving internal APIs, operational reporting systems, and data exchange services across distributed platforms.

• Maintained recurring monitoring scripts, validation routines, and automated quality assurance workflows supporting long-term operational consistency.

• Collaborated with engineering and analytics teams on reporting initiatives, infrastructure improvements, and scalable data processing enhancements. Data Analyst

Harris Corporation Melbourne, FL Nov 2013 – Apr 2014

• Built operational dashboards, recurring reports, and analytical workflows using SQL, Python, and spreadsheet-based reporting processes.

• Developed data cleansing, validation, and transformation workflows improving reporting consistency and operational dataset quality.

• Assisted with ETL workflows, API-driven data extraction processes, and recurring database analysis tasks supporting internal analytics initiatives.

• Worked with PostgreSQL, MySQL, and SQL Server environments to prepare datasets for operational reporting and business intelligence workflows.

• Applied statistical analysis, trend analysis, and exploratory data profiling methods to identify operational inconsistencies and reporting gaps.

• Supported engineering and analytics teams with recurring reporting maintenance, data mapping activities, and validation workflow improvements.

• Created reusable SQL scripts, reporting templates, and automated analysis workflows streamlining recurring operational reporting requests.

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