Looks like you have JavaScript disabled. For the full Twine experience, you will need to re-enable it.

I am a senior AI/ML engineer with a decade of experience designing, deploying, and scaling machine learning systems across healthcare, fintech, and enterprise data platforms. I specialize in Python, deep learning, MLOps, and cloud-based AI solutions, and I enjoy turning complex data challenges into reliable, compliant production systems. I’ve led end-to-end pipelines, integrated GenAI/LLMs, and built governance and observability into data workflows. I’m passionate about collaboration, mentoring teams, and delivering value through practical AI that respects privacy and regulatory requirements.…I am a senior AI/ML engineer with a decade of experience designing, deploying, and scaling machine learning systems across healthcare, fintech, and enterprise data platforms. I specialize in Python, deep learning, MLOps, and cloud-based AI solutions, and I enjoy turning complex data challenges into reliable, compliant production systems. I’ve led end-to-end pipelines, integrated GenAI/LLMs, and built governance and observability into data workflows. I’m passionate about collaboration, mentoring teams, and delivering value through practical AI that respects privacy and regulatory requirements.

Michael Clayton

AI Engineer, Data Scientist, Developer, +2





I am a senior AI/ML engineer with a decade of experience designing, deploying, and scaling machine learning systems across healthcare, fintech, and enterprise data platforms. I specialize in Python, deep learning, MLOps, and cloud-based AI solutions, and I enjoy turning complex data challenges into reliable, compliant production systems. I’ve led end-to-end pipelines, integrated GenAI/LLMs, and built governance and observability into data workflows. I’m passionate about collaboration, mentoring teams, and delivering value through practical AI that respects privacy and regulatory requirements.…I am a senior AI/ML engineer with a decade of experience designing, deploying, and scaling machine learning systems across healthcare, fintech, and enterprise data platforms. I specialize in Python, deep learning, MLOps, and cloud-based AI solutions, and I enjoy turning complex data challenges into reliable, compliant production systems. I’ve led end-to-end pipelines, integrated GenAI/LLMs, and built governance and observability into data workflows. I’m passionate about collaboration, mentoring teams, and delivering value through practical AI that respects privacy and regulatory requirements.

Available to hire

I am a senior AI/ML engineer with a decade of experience designing, deploying, and scaling machine learning systems across healthcare, fintech, and enterprise data platforms. I specialize in Python, deep learning, MLOps, and cloud-based AI solutions, and I enjoy turning complex data challenges into reliable, compliant production systems.

I’ve led end-to-end pipelines, integrated GenAI/LLMs, and built governance and observability into data workflows. I’m passionate about collaboration, mentoring teams, and delivering value through practical AI that respects privacy and regulatory requirements.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Language

English

Fluent

Work Experience

Lead AI/ML Engineer at OmniData LLC

July 1, 2025 - July 1, 2025

Led end-to-end AI/ML pipelines for data integration, governance, and large-scale deployment. Architected workflows using Airflow, Spark, Snowflake, BigQuery, AWS (S3/Glue/Redshift), GCP (Vertex AI). Built feature stores (PostgreSQL, Redis) and automated MLOps pipelines with Kubeflow and MLflow. Integrated LLMs/GenAI using Hugging Face, LangChain, FAISS, Pinecone for natural language querying. Deployed ML services as Docker/Kubernetes microservices with CI/CD via GitHub Actions, ArgoCD. Implemented data governance & observability using Apache Ranger, OpenLineage, Great Expectations, EvidentlyAI, WhyLabs. Applied privacy-preserving ML (federated learning, differential privacy) across sensitive datasets. Delivered executive insights with Power BI, Streamlit, and trained teams on MLOps & GenAI adoption.

Senior AI/ML Engineer at IWP Capital

June 1, 2020 - June 1, 2020

Designed fraud/risk ML pipelines with XGBoost, PyTorch, Spark Streaming, Kafka. Built time-series forecasting models (LSTM) and NLP models (BERT, spaCy) for chat and claims classification. Applied graph ML (PyTorch Geometric, NetworkX) for fraud network detection and SHAP for explainable ML. Deployed ML APIs via Docker/Kubernetes, migrated workloads to AWS SageMaker, and automated retraining with CI/CD (Jenkins, GitHub Actions). Optimized PostgreSQL/Redshift schemas for feature stores and delivered dashboards in Plotly Dash. Ensured GDPR & Basel III compliance through PII masking, encryption, and regulatory stress tests.

Machine Learning Engineer at IDEXX

October 1, 2018 - October 1, 2018

Built predictive models (Random Forests, Gradient Boosting, Logistic Regression) for patient outcome forecasting. Developed ETL pipelines with Python, SQL, Spark for HIPAA-compliant healthcare data. Applied NLP (TF-IDF, LDA, word2vec) and CNNs in TensorFlow for clinical notes and imaging analysis. Automated feature engineering with Scikit-learn, reducing retraining cycles. Deployed ML scoring services with Flask REST APIs, enabling real-time clinical decision support. Created visualization tools in Tableau, matplotlib and optimized SQL queries for large-scale retrieval. Enforced PHI/PII anonymization to maintain privacy and compliance.