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Hi, I'm Andrew James Lytle—a Senior Full-Stack AI Engineer specializing in machine learning and large language models. I design, train, and deploy production-ready ML systems and LLM-enabled features, collaborating with cross-functional teams to turn ideas into reliable, measurable AI outcomes. I'm passionate about mentoring junior engineers, conducting thoughtful code reviews, and sharing best practices to elevate engineering standards. I build scalable, secure AI pipelines with robust data preprocessing, evaluation, deployment, and continuous optimization, driving AI solutions from concept to production while exceeding project expectations.…Hi, I'm Andrew James Lytle—a Senior Full-Stack AI Engineer specializing in machine learning and large language models. I design, train, and deploy production-ready ML systems and LLM-enabled features, collaborating with cross-functional teams to turn ideas into reliable, measurable AI outcomes. I'm passionate about mentoring junior engineers, conducting thoughtful code reviews, and sharing best practices to elevate engineering standards. I build scalable, secure AI pipelines with robust data preprocessing, evaluation, deployment, and continuous optimization, driving AI solutions from concept to production while exceeding project expectations.

Andrew James Lytle

Full Stack Developer, Back-End Developer, Web Developer, +6

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Hi, I'm Andrew James Lytle—a Senior Full-Stack AI Engineer specializing in machine learning and large language models. I design, train, and deploy production-ready ML systems and LLM-enabled features, collaborating with cross-functional teams to turn ideas into reliable, measurable AI outcomes. I'm passionate about mentoring junior engineers, conducting thoughtful code reviews, and sharing best practices to elevate engineering standards. I build scalable, secure AI pipelines with robust data preprocessing, evaluation, deployment, and continuous optimization, driving AI solutions from concept to production while exceeding project expectations.…Hi, I'm Andrew James Lytle—a Senior Full-Stack AI Engineer specializing in machine learning and large language models. I design, train, and deploy production-ready ML systems and LLM-enabled features, collaborating with cross-functional teams to turn ideas into reliable, measurable AI outcomes. I'm passionate about mentoring junior engineers, conducting thoughtful code reviews, and sharing best practices to elevate engineering standards. I build scalable, secure AI pipelines with robust data preprocessing, evaluation, deployment, and continuous optimization, driving AI solutions from concept to production while exceeding project expectations.

Available to hire

Hi, I’m Andrew James Lytle—a Senior Full-Stack AI Engineer specializing in machine learning and large language models. I design, train, and deploy production-ready ML systems and LLM-enabled features, collaborating with cross-functional teams to turn ideas into reliable, measurable AI outcomes.

I’m passionate about mentoring junior engineers, conducting thoughtful code reviews, and sharing best practices to elevate engineering standards. I build scalable, secure AI pipelines with robust data preprocessing, evaluation, deployment, and continuous optimization, driving AI solutions from concept to production while exceeding project expectations.

Skills

Experience Level

Expert

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Intermediate

Work Experience

Senior Full-Stack Engineer at DataRobot

July 1, 2022 - Present

Led full-stack development of DataRobot's enterprise AI platform, building secure, scalable backend services using Python (FastAPI & Django) and interactive UIs with React and TypeScript. Designed and implemented enterprise-grade RESTful APIs to support model lifecycle management, data ingestion, and secure access to prediction services. Developed real-time analytics dashboards by exposing Python-based data aggregation APIs consumed by React + Chart.js, visualizing model performance, prediction trends, and data drift metrics. Architected and deployed Python microservices using Docker and Kubernetes on AWS ECS/EKS, reducing deployment time by 40% and increasing platform scalability by 30%. Integrated Apache Kafka into Python services to handle real-time ML events across the platform. Replaced monolithic services with modular Python-based microservices for model registry, prediction serving, user authentication, and data ingestion, improving maintainability and scalability. Leveraged Pos

Full-Stack Engineer at Replit

February 1, 2018 - June 1, 2022

Developed backend services in Python (Flask & FastAPI) powering Replit's cloud-based developer platform, handling project execution, workspace state, and user sessions. Built RESTful APIs for internal tooling and UI features, enabling seamless interaction between backend services and the React-based web IDE. Contributed to Replit's AI-powered coding assistance by designing Python microservices for usage analysis and code generation recommendations. Refactored endpoints and middleware to improve API efficiency (25% reduction in frontend errors). Established CI/CD pipelines (AWS, Docker, GitHub Actions). Optimized SQL queries via indexing and parameterization, reducing API latency. Implemented OAuth 2.0 and JWT authentication for core services. Supported real-time analytics dashboards tracking workspace usage and collaboration. Migrated critical services to a microservices architecture with Docker. Built test harnesses with Pytest to improve coverage. Mentored juniors; collaborated acros

Senior AI Engineer at DataRobot

July 1, 2022 - Present

Led end-to-end development of DataRobot’s AI-driven data management platform, designing and deploying production-ready ML pipelines with automated feature engineering, model selection, and hyperparameter optimization at scale. Built model explainability workflows using SHAP and prediction explanations to meet regulatory requirements. Implemented MLOps practices including model versioning, automated retraining, drift detection, and performance monitoring, improving lifecycle governance in production. Developed real-time and batch inference services via REST APIs and containerized deployments for low-latency enterprise predictions. Integrated external data sources (SQL, Snowflake, S3, Kafka) into pipelines to support large-scale data ingestion and continuous learning. Collaborated with data scientists and product teams to translate business requirements into deployable AI solutions, optimized feature selection, ensemble strategies, and cross-validation to improve accuracy and stability

ML Engineer at Replit

February 1, 2018 - June 1, 2022

Contributed to AI-powered features including code completion, code analysis, and personalized coding suggestions. Led backend development of ML pipelines for data preprocessing, feature engineering, model training, and evaluation for AI-assisted coding workflows. Designed and implemented real-time analytics dashboards to monitor model performance, usage, and prediction accuracy, enabling data-driven improvements. Developed deployment pipelines using Docker, Kubernetes, and AWS for scalable, low-latency inference. Built automated testing frameworks for ML models to ensure reliability and reduce production bugs. Refactored large-scale data processing workflows with SQL, Pandas, and Spark to improve data throughput and training efficiency. Collaborated with DevOps to streamline CI/CD for ML deployments and integrated secure authentication (OAuth 2.0) to protect user data.