Principal ML Engineer - Enterprise AI Leader, Healthcare ML and MLOps

Kevin Joshua Hires

PRINCIPAL ML ENGINEER LEAD ML ENGINEER SENIOR ML ENGINEER

Dunwoody, GA I *****.******.*****@*******.***

Principal ML Engineer with 8 years of uninterrupted tenure at Delta Dental, one of the largest dental benefits providers in the US, progressing from the company's first production ML pipelines to enterprise- wide AI authority across 12 engineering teams and 10M+ members. Combines deep technical execution in healthcare claims ML, GenAI platform architecture, and MLOps governance with the leadership depth to align C-suite stakeholders, grow engineering teams, and shape industry AI standards through WEDI and AHIP working groups.

Healthcare ML – GenAI & RAG Systems - Fraud Detection - MLOps Platform - Team Leadership - HIPAA Compliance PROFESSIONAL EXPERIENCE

PRINCIPAL MACHINE LEARNING ENGINEER

Delta Dental Insurance I San Francisco, California 04/2024 – 05/2026

● Elevated to the company's top technical AI role, accountable for the full enterprise AI agenda at Delta Dental. This included owning the build/buy/partner decision framework, evaluating every architecture proposal and vendor AI product across 12 engineering teams, and defining a 3-year capability roadmap that was ratified at C-suite level and aligned to measurable business outcomes across the dental benefits portfolio.

● Designed and led delivery of a GenAI member experience platform using RAG over curated dental benefits knowledge bases, with fine-tuned LLMs, LangChain orchestration, FAISS vector search, and real-time FastAPI integration into live claims and eligibility systems. Projected to deflect 25% of call-center volume from a 10M+ member base, translating to approximately $4M in annual operational savings.

● Stood up the company's first enterprise MLOps governance framework covering deployment standards, drift detection, and model risk management across 12 teams. Production model incidents dropped 60% in the first year, and every AI initiative now passes through a formal risk review process owned at the principal level before reaching production.

● Ran an AI coding assistant pilot across 200+ engineers that measured a 20% productivity gain and 15% shorter code review cycles. Built and published Delta Dental's responsible AI principles as the foundation of all future model and GenAI work, covering explainability, fairness, and regulatory alignment with state insurance requirements.

● Represented Delta Dental in WEDI and AHIP AI working groups, contributing to draft industry guidance on responsible AI in dental benefits adjudication. Sponsored 4 senior and lead engineers on structured development plans, with 2 achieving promotion within 18 months, a deliberate investment in the leadership pipeline beneath the principal level. LEAD MACHINE LEARNING ENGINEER

Delta Dental Insurance I San Francisco, California 08/2022 – 04/2024

● Took ownership of Delta Dental's ML platform buildout as the organization's first dedicated ML lead, moving the team from ad hoc project delivery to a governed engineering discipline. Centralized infrastructure including a feature store, model registry, and real-time monitoring layer shrank time-to-production from 6 weeks to 9 days, a 6x improvement that compounded across every team shipping models.

● Architected an LLM-powered document understanding system for Explanation of Benefits processing, applying transformer-based semantic extraction to automate structured data capture from complex insurance documents. The system reduced manual review FTEs by 30%, freeing clinical operations staff for higher-judgment work that automated extraction could not handle.

● Wrote and executed an 18-month ML roadmap across 4 product lines, bringing 3 VPs to alignment on AI investment priorities and unlocking budget for platform expansion and team growth. Introduced automated drift detection and performance monitoring across all deployed models, cutting production incidents by 60% and eliminating the reactive firefighting that had consumed significant engineering capacity.

● Scaled the team from 3 to 6 engineers through structured hiring and onboarding, doubling sprint velocity through targeted process improvements and hands-on technical mentorship. Built and owned the model governance and bias auditing framework adopted as the company standard in response to state insurance regulatory requirements covering all member-facing ML models. SENIOR MACHINE LEARNING ENGINEER

Delta Dental Insurance I San Francisco, California 10/2020 – 08/2022

● Led the Claims Intelligence Platform, Delta Dental's most comprehensive ML deployment at the time, delivering a hybrid fraud detection system that combined XGBoost and Random Forest ensemble models with domain-driven rule logic. The system reached 91% precision and cut false positives by 34% versus the prior rule-only approach, directly preventing an estimated $2.8M in fraudulent payouts each year.

● Re-engineered the claims data infrastructure on AWS Glue and PySpark, applying partition pruning, broadcast joins, and query plan optimization to slash pipeline runtime by 62% and unlock same-day fraud scoring across 500K+ daily claims. Exposed all ML models through REST APIs on AWS, tripling real-time scoring throughput and enabling automated adjudication decisions at the point of claim intake.

● Built patient and provider risk scoring frameworks from 3 years of historical claims and utilization data, using clustering to segment behavior into risk tiers that focused investigator effort on the highest-priority cases across a 10M+ member base. An NLP extraction pipeline on clinical notes and EOB documents reduced manual claims review workload by 40% by surfacing structured fields that previously required analyst interpretation.

● Owned fraud KPI reporting for 5 business units through Power BI and Tableau dashboards that became the primary operational reporting layer across the organization. Maintained full HIPAA compliance across all model and data pipelines through AWS IAM controls and audit-ready documentation, closing the project lifecycle with zero compliance incidents over the full 2-year engagement.

MACHINE LEARNING ENGINEER

Delta Dental Insurance I San Francisco, California 06/2018 – 10/2020

● Shipped Delta Dental's first production ML system, a dental claim auto-adjudication model that moved straight-through processing from 54% to 71%, cutting the manual review queue significantly and establishing the ML engineering practice from scratch. Paired it with an NLP pipeline that extracted procedure codes and clinical variables directly from unstructured provider notes, saving the claims operations team 15hrs of manual extraction work per week.

● Migrated all batch scoring from single-node Python to distributed PySpark on Amazon EMR, cutting model training time by 40% and scaling record throughput by 10x. Built the team's first HIPAA-compliant feature engineering layer on AWS Glue, producing reusable feature sets across member risk, claims frequency, and provider behavior that became the shared foundation for every model built afterward.

● Introduced a structured A/B testing and model evaluation framework that was adopted by 3 product teams, replacing gut-driven rollout decisions with data-grounded release gates. Worked closely with actuarial and regulatory teams from day one to embed ML-safe constraints into every model, a practice that carried forward through all subsequent work at the company. EDUCATION

BACHELOR OF SCIENCE, COMPUTER SCIENCE

Virginia Tech, Blacksburg, VA 2014 – 2018

TECHNICAL SKILLS

ML and AI: Machine Learning, XGBoost, Random Forest, Logistic Regression, Scikit-Learn, Anomaly Detection, Fraud Detection, Risk Scoring, Clustering, A/B Testing, Feature Engineering, Natural Language Processing (NLP)

GenAI and LLMs: Generative AI, Retrieval-Augmented Generation (RAG), LLM Fine-Tuning, LangChain, Prompt Engineering, Vector Search, Enterprise AI Strategy, Responsible AI MLOps and Data: MLOps at Scale, MLflow, Model Governance, Apache Spark, PySpark, AWS Glue, Amazon Elastic MapReduce (EMR), Claims Analytics, Python, SQL, REST APIs Cloud and Compliance: Amazon Web Services (AWS), Kubernetes, Docker, Microsoft Power BI, Tableau, HIPAA, Stakeholder Management, Executive-level Communication, Thought Leadership, Mentoring

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