Senior Systems & ML Infrastructure Engineer

Dennis De St Jeor

*** *** ******, ******, ************ 16668

904-***-**** : ******.********@*****.***

Summary

Engineer focused on building and scaling high-performance production systems across AWS and GCP, with deep experience in distributed systems, AI/ML deployment, and GPU-accelerated computing. Proven track record of transforming research and prototype systems into scalable, production-ready platforms, including 40 performance gains in medical AI workloads. Experience spans healthcare AI, predictive maintenance, and cybersecurity.

Technical Skills

● Languages & Frameworks: Python, C/C++, TypeScript, Django, Flask, Tornado, Next.js, Angular, Prisma

● Cloud & Infrastructure: AWS (EC2, RDS, Redshift, QuickSight), GCP, Docker, Kubernetes, Terraform, Ansible

● Data & Systems: PostgreSQL, Elasticsearch, Redis, RabbitMQ

● AI/ML & Performance: GPU Computing (CUDA), ML Inference Pipelines, Distributed Systems, Performance Optimization

Highlander Today

Founder & Product Engineer Patton, PA Mar 2025 to Present

● Designed and built a multi-tenant community platform from the ground up using Next.js, TypeScript, PostgreSQL, and Prisma

● Integrating AI-assisted writing tools to support journalists and contributors in article creation and editing workflows

● Delivered core product features including content publishing, events, marketplace listings, messaging, and directory discovery

● Implemented role-based permissions, tenant-scoped access controls, and moderation workflows to ensure trust and safety across independent community instances

● Built internal admin tooling for user management, content moderation, and platform operations, enabling efficient day-to-day oversight

● Engineered shared platform infrastructure including file upload pipelines, rich content editing, and reusable APIs designed for stability during rapid iteration

● Launched to production with real users and live community engagement Johnson & Johnson

Contractor - Remote Sep 2024 Mar 2025 Software Engineer

● Led optimization of AI pipeline for endoscopic tumor detection, achieving 40 performance improvement through GPU acceleration (CUDA) on AWS EC2, reducing analysis time from hours to minutes

● Transformed META AI research code into production-grade system, deploying scalable inference workloads across GPU and CPU environments in AWS

● Engineered high-performance Python inference pipeline, reducing latency and improving throughput for video-based medical diagnosis workflows

● Built and deployed CI/CD infrastructure using Terraform, Jenkins, Docker, and Kubernetes, enabling repeatable and reliable production releases

● Implemented monitoring and performance tuning across distributed infrastructure to ensure system stability under production load

Center for Open Science

Backend & GCP Engineer Charlottesville, VA May 2023 - Sept 2024

● Led infrastructure cost analysis of a decade-old platform, identifying and driving 7% annual cost reduction through architectural consolidation and GCP resource optimization

● Designed and built Data Science analytics environment end-to-end, including tooling setup, training materials, and reusable query library to enable team-wide adoption

● Developed and maintained backend services in Python (Django, Flask) with PostgreSQL and Elasticsearch, deployed on Kubernetes within GCP

● Served as Scrum Master for 8 months while maintaining full engineering responsibilities, improving team delivery cadence and coordination

● Established Confluence based engineering documentation standards across Product and Engineering, reducing onboarding friction and improving cross-team consistency Sentient Science

Software Solutions Architec Buffalo NY December 2021 - Apr 2023

● Architected and led development of a full-stack predictive maintenance platform for the U.S. Army’s Future Vertical Lift (SBIR) program, enabling modeling of aircraft drivetrain component lifespan and maintenance forecasting

● Designed end-to-end system architecture across frontend (Angular), middleware (Django, Tornado, RabbitMQ), and backend (PostgreSQL, AWS Redshift), establishing core technology and integration decisions for production-scale deployment

● Built GPU-accelerated analysis modules using Python and CUDA on AWS EC2 to support compute-intensive materials science workloads

● Developed interactive analytics dashboards using Redshift and QuickSight, enabling engineering and program stakeholders to visualize component degradation and predictive insights

● Designed and implemented REST APIs integrating internal systems and external vendor data sources to support complex data pipelines

● Deployed and managed infrastructure using Ansible, Gunicorn, and Nginx, establishing repeatable build and deployment patterns

Raytheon Intelligence And Space

Senior Cyber Engineer, Cyber Security Washington D.C October 2014 - December 2021

● Developed and maintained cybersecurity software systems supporting government agencies, Department of Defense, and financial institutions in high-security, mission-critical environments

● Key contributor to development of a patented active threat hunting system leveraging machine learning techniques to continuously analyze network activity across large-scale environments (hundreds to thousands of devices)

● Designed decentralized, autonomous threat detection components ("headless hunter" systems) capable of operating without centralized control, improving system resilience and enabling distributed threat analysis across network nodes

● Built data analysis tools to process and visualize complex cybersecurity datasets, enabling identification of patterns, anomalies, and potential threats

● Contributed to development of scalable backend systems and data processing pipelines supporting real-time and near real-time threat detection workflows

General Electric Transportation R&D

R&D Software Engineer Jacksonville, FL March 2014 - August 2014

● Developed a proprietary embedded solution for custom handheld devices to scan, analyze, and validate signal box configurations against known secure baselines, enabling verification of system integrity in the field

● Engineered communication stack to dynamically interface with heterogeneous and previously unknown device configurations

● Built adaptive parsing framework capable of recognizing and processing multiple data formats (XML, YAML, JSON) across variable input structures

● Designed comparison algorithms to validate expected vs. actual system configurations, identifying unknown, invalid, or improperly placed components

Education

Economics

Oregon State University - Corvallis, OR, USA

Business Finance

Oregon State University - Corvallis, OR, USA

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