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Lead engineer with 10+ years of experience building and deploying production software systems across AI-powered healthcare, global workforce platforms, and enterprise insurance. Strong foundation in Python, PyTorch, TensorFlow, and SQL, with hands-on AWS, Docker, and Kubernetes, delivering end-to-end MLOps from experimentation through deployment and monitoring. Known for pragmatic, production-quality engineering and clear communication with technical and non-technical stakeholders. Experienced in building scalable data pipelines, ML services, and APIs while improving inference performance, reliability, and latency, and mentoring teams on repeatable AI/ML delivery practices.…Lead engineer with 10+ years of experience building and deploying production software systems across AI-powered healthcare, global workforce platforms, and enterprise insurance. Strong foundation in Python, PyTorch, TensorFlow, and SQL, with hands-on AWS, Docker, and Kubernetes, delivering end-to-end MLOps from experimentation through deployment and monitoring. Known for pragmatic, production-quality engineering and clear communication with technical and non-technical stakeholders. Experienced in building scalable data pipelines, ML services, and APIs while improving inference performance, reliability, and latency, and mentoring teams on repeatable AI/ML delivery practices.

Mario Tee

Software Engineer, Data Scientist, AI Engineer, +2

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Lead engineer with 10+ years of experience building and deploying production software systems across AI-powered healthcare, global workforce platforms, and enterprise insurance. Strong foundation in Python, PyTorch, TensorFlow, and SQL, with hands-on AWS, Docker, and Kubernetes, delivering end-to-end MLOps from experimentation through deployment and monitoring. Known for pragmatic, production-quality engineering and clear communication with technical and non-technical stakeholders. Experienced in building scalable data pipelines, ML services, and APIs while improving inference performance, reliability, and latency, and mentoring teams on repeatable AI/ML delivery practices.…Lead engineer with 10+ years of experience building and deploying production software systems across AI-powered healthcare, global workforce platforms, and enterprise insurance. Strong foundation in Python, PyTorch, TensorFlow, and SQL, with hands-on AWS, Docker, and Kubernetes, delivering end-to-end MLOps from experimentation through deployment and monitoring. Known for pragmatic, production-quality engineering and clear communication with technical and non-technical stakeholders. Experienced in building scalable data pipelines, ML services, and APIs while improving inference performance, reliability, and latency, and mentoring teams on repeatable AI/ML delivery practices.

Available to hire

Lead engineer with 10+ years of experience building and deploying production software systems across AI-powered healthcare, global workforce platforms, and enterprise insurance. Strong foundation in Python, PyTorch, TensorFlow, and SQL, with hands-on AWS, Docker, and Kubernetes, delivering end-to-end MLOps from experimentation through deployment and monitoring.

Known for pragmatic, production-quality engineering and clear communication with technical and non-technical stakeholders. Experienced in building scalable data pipelines, ML services, and APIs while improving inference performance, reliability, and latency, and mentoring teams on repeatable AI/ML delivery practices.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Work Experience

Lead Engineer at Tempus AI

March 1, 2023 - Present

Led development of AI-powered healthcare products that support clinicians through clinical assistants and knowledge-driven workflows. Built and deployed production ML models using PyTorch and TensorFlow for clinical decision support, and designed scalable pipelines for clinical and genomic data to enable precision medicine insights. Architected and deployed ML services on AWS with Docker and Kubernetes, setting up CI/CD for reliable model deployment, rollback, and governance. Implemented MLOps practices including model versioning, experiment tracking, and automated monitoring to ensure production reliability and performance. Optimized inference performance and latency for voice-enabled clinical experiences (e.g., quantization and serving improvements). Established model evaluation frameworks and A/B testing for safe, accurate rollouts; built REST APIs and backend integrations to connect models with clinical workflows; and delivered observability/alerting that reduced incident response

Senior Software Engineer at Deel

May 1, 2020 - February 1, 2023

Worked on a global workforce platform supporting hiring, management, and payment of employees and contractors with payroll and compliance workflows. Built and deployed ML models using Python and TensorFlow to automate manual steps in payroll/compliance processes, improving processing time and accuracy. Designed scalable data pipelines for international workforce and financial data to support real-time operational insights. Developed production ML services on AWS using Docker and Kubernetes with CI/CD for automated testing and deployment of model updates. Implemented model monitoring and versioning for performance tracking and rapid rollback. Optimized backend integrations and API performance for high-volume transactions, improving reliability and reducing latency. Collaborated cross-functionally with product, data, and engineering teams across global stakeholders, ensuring solutions met reliability, scalability, and compliance requirements.

Software Engineer at Kemper

May 1, 2015 - April 1, 2020

Contributed to enterprise insurance platforms covering policy management, claims processing, customer servicing, reporting, and analytics. Helped modernize legacy systems by building data pipelines and ETL processes to improve how insurance data moved across the organization. Developed ML models using Python and TensorFlow for risk analysis, fraud detection, and decision-making initiatives. Built and deployed ML services using Docker on AWS while establishing foundational MLOps practices. Implemented REST APIs and backend integrations connecting analytical models to insurance workflows. Designed scalable data processing solutions to improve reliability and performance for critical operations, collaborated on feature engineering pipelines for predictive risk models, and supported code review/documentation practices to improve code quality and knowledge sharing.