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I'm an AI Engineer specializing in AI training, data annotation, and content moderation for large-scale, production-grade AI systems. I annotate, label, and review diverse data to improve model accuracy and reliability, and I design end-to-end pipelines and evaluation frameworks that scale with multi-terabyte healthcare datasets. I collaborate across product, compliance, and leadership teams, mentor engineers, and maintain clear annotation guidelines and documentation to support continuous improvement in AI training, prompt engineering, and deployment in distributed environments.…I'm an AI Engineer specializing in AI training, data annotation, and content moderation for large-scale, production-grade AI systems. I annotate, label, and review diverse data to improve model accuracy and reliability, and I design end-to-end pipelines and evaluation frameworks that scale with multi-terabyte healthcare datasets. I collaborate across product, compliance, and leadership teams, mentor engineers, and maintain clear annotation guidelines and documentation to support continuous improvement in AI training, prompt engineering, and deployment in distributed environments.

Ryan Daily

AI Engineer, Data Scientist, Full Stack Developer, +2

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I'm an AI Engineer specializing in AI training, data annotation, and content moderation for large-scale, production-grade AI systems. I annotate, label, and review diverse data to improve model accuracy and reliability, and I design end-to-end pipelines and evaluation frameworks that scale with multi-terabyte healthcare datasets. I collaborate across product, compliance, and leadership teams, mentor engineers, and maintain clear annotation guidelines and documentation to support continuous improvement in AI training, prompt engineering, and deployment in distributed environments.…I'm an AI Engineer specializing in AI training, data annotation, and content moderation for large-scale, production-grade AI systems. I annotate, label, and review diverse data to improve model accuracy and reliability, and I design end-to-end pipelines and evaluation frameworks that scale with multi-terabyte healthcare datasets. I collaborate across product, compliance, and leadership teams, mentor engineers, and maintain clear annotation guidelines and documentation to support continuous improvement in AI training, prompt engineering, and deployment in distributed environments.

Available to hire

I’m an AI Engineer specializing in AI training, data annotation, and content moderation for large-scale, production-grade AI systems. I annotate, label, and review diverse data to improve model accuracy and reliability, and I design end-to-end pipelines and evaluation frameworks that scale with multi-terabyte healthcare datasets.

I collaborate across product, compliance, and leadership teams, mentor engineers, and maintain clear annotation guidelines and documentation to support continuous improvement in AI training, prompt engineering, and deployment in distributed environments.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Fluent

Work Experience

AI Engineer at Point C

January 1, 2024 - Present

Built and operated a production-grade LLM-powered platform for clinical review automation, prior authorization, and pharmacy benefit validation; processed multi-terabyte healthcare datasets; designed scalable Python/FastAPI backends and event-driven pipelines with AWS SQS/Step Functions; integrated LangChain-based RAG pipelines and FAISS-powered semantic search; implemented multi-agent LLM workflows, ETL and data labeling pipelines using Airflow, Spark, Snowflake, and S3; tuned models with LoRA and Hugging Face workflows; deployed on AWS SageMaker; established MLOps with MLflow, CI/CD, and observability; ensured HIPAA-compliant data privacy; led annotation guidelines and remote teams.

AI/ML Engineer, Data Scientist at GoHealth

June 1, 2019 - December 1, 2023

Designed and deployed ML/LLM-powered decision systems for health plan matching, enrollment optimization, and denial resolution on large healthcare datasets; built predictive models (XGBoost, PyTorch, scikit-learn); reduced denial resolution time by 32%; developed RAG-based decision support with LangChain, OpenAI, and FAISS; fine-tuned ClinicalBERT for structured data extraction; conducted A/B experiments and drift monitoring; built scalable Spark/Snowflake/Databricks pipelines for real-time inference and retraining; implemented ML lifecycle tooling (MLflow, Azure ML); applied SHAP explanations; collaborated with product and business stakeholders.

Full Stack Developer & Machine Learning Engineer at CNO Financial Group

September 1, 2016 - May 31, 2019

Contributed to predictive analytics and decision-support systems for underwriting and risk management; built churn/policy modeling; improved data quality with SQL ETL; developed PySpark and Airflow pipelines; ingested data into Azure Data Lake; optimized Spark jobs; built backend APIs with Python (FastAPI/Flask) and dashboards with React; designed relational data models and SQL Server queries; deployed containerized apps on AKS; partnered with actuarial and data science teams to translate business requirements into data-driven solutions.