Michael Eniolade

Salem, OR

Open to Relocation

Software Engineer and Data Scientist with 10+ years of experience designing, building, and deploying data pipelines, machine learning models, and cloud-native solutions across healthcare, telecom, government, and education sectors. Currently pursuing a Ph.D. in Information Technology at the University of the Cumberlands, focusing on applying AI and machine learning to healthcare cybersecurity, anomaly detection, and IoT security.

Strong expertise in AWS, Azure, and GCP, with deep knowledge of infrastructure management, data warehousing, serverless computing, and CI/CD automation. Experienced in developing distributed applications with Spark/PySpark, Snowflake, and Data Lakehouse architectures, ensuring scalability and high availability. Skilled in Machine Learning and AI, including Scikit-learn, TensorFlow, PyTorch, Hugging Face, LLMs, Generative AI, and LangChain, with hands-on experience in MLOps tools such as MLflow, Docker, Kubernetes, GitHub Actions, and Terraform.

news

Mar 01, 2026	Published multiple research articles on Generative AI and LLMs for healthcare, including patient engagement, EHR integration, and responsible AI for resource allocation.
Jan 15, 2026	Co-authored paper StepShield: When, Not Whether to Intervene on Rogue Agents published on arXiv (2601.22136).
Nov 01, 2025	Joined Mercor Intelligence as a Senior Software Engineer, working on AI coding model evaluation and SWE-Bench Pro V2 annotation.

latest posts

Mar 25, 2026	Integrating LLMs into Electronic Health Records
Mar 15, 2026	Generative AI and LLMs in U.S. Healthcare: Opportunities and Challenges
Feb 15, 2026	Responsible AI for Healthcare Resource Allocation

selected publications

Generative AI and Large Language Models for Patient Engagement and Policy Development in U.S. Healthcare

Michael Eniolade

Data Science and Big Data Analysis, Mar 2026

Bib

@article{eniolade2026genai_healthcare,
  title = {Generative AI and Large Language Models for Patient Engagement and Policy Development in U.S. Healthcare},
  author = {Eniolade, Michael},
  journal = {Data Science and Big Data Analysis},
  year = {2026},
  month = mar,
}

Integrating Large Language Models into EHRs for Patient Engagement and Education

Michael Eniolade

Data Science and Big Data Analysis, Mar 2026

Bib

@article{eniolade2026llm_ehr,
  title = {Integrating Large Language Models into EHRs for Patient Engagement and Education},
  author = {Eniolade, Michael},
  journal = {Data Science and Big Data Analysis},
  year = {2026},
  month = mar,
}

arXiv

StepShield: When, Not Whether to Intervene on Rogue Agents

Gloria Felicia, Michael Eniolade, Jinfeng He, and 3 more authors

Jan 2026

Bib

@article{felicia2026stepshield,
  title = {StepShield: When, Not Whether to Intervene on Rogue Agents},
  author = {Felicia, Gloria and Eniolade, Michael and He, Jinfeng and Sasindran, Zitha and Kumar, H. and Angati, M. H.},
  year = {2026},
  month = jan,
  archiveprefix = {arXiv},
}