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Built, trained, deployed, and optimized deep learning models using PyTorch, TensorFlow, and Scikit-learn for production AI in cloud environments. Designed and operated scalable data processing pipelines and MLOps workflows using SQL, Python, Docker, and Kubernetes to manage model lifecycles. Developed and maintained machine learning APIs, automated CI/CD workflows, and monitored model performance for reliability and speed improvements. Collaborated with software, product, and data teams to integrate AI models into AWS and GCP services with high availability, scalability, and clear communication across stakeholders…Built, trained, deployed, and optimized deep learning models using PyTorch, TensorFlow, and Scikit-learn for production AI in cloud environments. Designed and operated scalable data processing pipelines and MLOps workflows using SQL, Python, Docker, and Kubernetes to manage model lifecycles. Developed and maintained machine learning APIs, automated CI/CD workflows, and monitored model performance for reliability and speed improvements. Collaborated with software, product, and data teams to integrate AI models into AWS and GCP services with high availability, scalability, and clear communication across stakeholders

Tremayne Smith

Data Engineer, Software Engineer, DevOps Developer, +1

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Built, trained, deployed, and optimized deep learning models using PyTorch, TensorFlow, and Scikit-learn for production AI in cloud environments. Designed and operated scalable data processing pipelines and MLOps workflows using SQL, Python, Docker, and Kubernetes to manage model lifecycles. Developed and maintained machine learning APIs, automated CI/CD workflows, and monitored model performance for reliability and speed improvements. Collaborated with software, product, and data teams to integrate AI models into AWS and GCP services with high availability, scalability, and clear communication across stakeholders…Built, trained, deployed, and optimized deep learning models using PyTorch, TensorFlow, and Scikit-learn for production AI in cloud environments. Designed and operated scalable data processing pipelines and MLOps workflows using SQL, Python, Docker, and Kubernetes to manage model lifecycles. Developed and maintained machine learning APIs, automated CI/CD workflows, and monitored model performance for reliability and speed improvements. Collaborated with software, product, and data teams to integrate AI models into AWS and GCP services with high availability, scalability, and clear communication across stakeholders

Available to hire

Built, trained, deployed, and optimized deep learning models using PyTorch, TensorFlow, and Scikit-learn for production AI in cloud environments. Designed and operated scalable data processing pipelines and MLOps workflows using SQL, Python, Docker, and Kubernetes to manage model lifecycles.

Developed and maintained machine learning APIs, automated CI/CD workflows, and monitored model performance for reliability and speed improvements. Collaborated with software, product, and data teams to integrate AI models into AWS and GCP services with high availability, scalability, and clear communication across stakeholders

Skills

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Expert

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Intermediate

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Beginner

Work Experience

Senior ML Engineer at Optum

July 1, 2021 - Present

Built and operated enterprise AI and machine learning platforms for e-commerce and healthcare with a focus on scalable model deployment, MLOps, and production reliability. Developed and optimized deep learning models using PyTorch, TensorFlow, and Scikit-learn; improved analytics speed and reliability. Designed automated data pipelines integrating batch and streaming data for training, inference, and reporting across AWS and GCP. Developed and deployed scalable model-serving APIs and implemented CI/CD with Docker and Kubernetes for automated deployment, monitoring, and rollback. Managed model registries, experiment tracking, and performance monitoring (MLflow and dashboards). Integrated services with AWS (SageMaker, Lambda, ECS, EKS) and collaborated cross-functionally to translate requirements into production-ready AI systems, improving uptime and reducing latency through proactive monitoring and optimization.

Senior Data Scientist at Tempus AI

June 1, 2019 - June 30, 2021

Developed healthcare analytics and AI platforms for precision medicine, clinical decision support, oncology research, and clinical data intelligence. Built clinical NLP pipelines for pathology reports, physician notes, lab results, and genomic reports using ClinicalBERT, BioBERT, RoBERTa, and spaCy, including entity extraction and terminology normalization. Created predictive models for patient stratification and treatment outcomes using Scikit-learn, XGBoost, TensorFlow 2.x, and PyTorch. Built reproducible pipelines using Python, SQL, Spark, and Airflow to integrate EHR, laboratory, and genomic datasets. Implemented semantic search and retrieval systems using sentence transformers and FAISS for evidence retrieval and question answering, optimized evaluation and inference performance, and supported HIPAA-compliant governance with documentation and deployment support.

Senior Machine Learning Engineer at eBay

July 1, 2016 - December 31, 2018

Developed machine learning and large-scale data platforms for marketplace search, personalized recommendations, fraud detection, seller intelligence, and customer engagement. Built ranking and recommendation models plus click-through prediction using Python, scikit-learn, XGBoost, and TensorFlow 1.x. Implemented NLP pipelines for query classification, product categorization, entity extraction, semantic matching, and content enrichment with spaCy, Word2Vec, and Elasticsearch. Built distributed training and feature processing pipelines using Spark, Hadoop, Kafka, Hive, and Airflow for scalable training and batch inference. Implemented evaluation, A/B testing, performance monitoring, and automated retraining workflows; optimized inference services and SQL workloads to reduce latency and improve scalability.

Data Engineer at Wayfair

May 1, 2014 - June 30, 2016

Built enterprise data platforms supporting customer analytics, product catalog management, merchandising, inventory optimization, and marketplace reporting. Designed scalable ETL/ELT pipelines using Python, SQL, Java, Hadoop/Hive, Spark, and Sqoop to process customer, product, inventory, order, and supplier data. Integrated transactional databases, clickstream events, logs, and third-party feeds into analytical warehouses. Developed dimensional models and reusable datasets for analytics. Implemented automated data validation, schema monitoring, reconciliation, and recovery procedures to improve data quality. Optimized SQL/Hive/Spark workloads through partitioning, indexing, incremental processing, and workflow tuning to improve performance and scalability.

AI Full Stack Engineer at LocalMed

January 1, 2013 - April 30, 2014

Developed patient-facing and provider-facing healthcare applications for real-time appointment scheduling, practice management integration, and secure communication. Built responsive web applications and REST APIs using Python, Java, JavaScript, jQuery, HTML5, CSS3, and standard web practices. Implemented backend integrations with medical/dental practice management systems to synchronize availability and booking in real time. Added scheduling validation and conflict detection with transactional database operations and automated email/SMS workflows. Collaborated with product, QA, and healthcare partners for testing, API integration, deployments, and iterative enhancements.