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Schedule Interview NowMy name is David L. and I have over 9 years of experience in the tech industry. I specialize in the following technologies: Python, 3D Modeling, C++, AWS Lambda, node.js, etc.. I hold a degree in Bachelor of Engineering (BEng). Some of the notable projects I’ve worked on include: Ad Nucleus UX/UI Design & Development, Precision Manufacturing CNC AI Pipeline & Fusion360 Add-In, iOS Medical Transcription and Billing Code Predictions. I am based in Hialeah, United States. I've successfully completed 3 projects while developing at Softaims.
I value a collaborative environment where shared knowledge leads to superior outcomes. I actively mentor junior team members, conduct thorough quality reviews, and champion engineering best practices across the team. I believe that the quality of the final product is a direct reflection of the team's cohesion and skill.
My experience at Softaims has refined my ability to effectively communicate complex technical concepts to non-technical stakeholders, ensuring project alignment from the outset. I am a strong believer in transparent processes and iterative delivery.
My main objective is to foster a culture of quality and accountability. I am motivated to contribute my expertise to projects that require not just technical skill, but also strong organizational and leadership abilities to succeed.
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Nvidia
Developed a React.js UX/UI for a programatic advertising platform.
Goal: build a secure, cost-efficient CNC Cloud that captures CAD/CAM user selections, streams them through an ETL lake, then trains & deploys ML models for real-time CNC predictions while exposing CRUD APIs with fine-grained auth. Solution: crafted single-table DynamoDB with generic partition endpoints, S3→Athena→SageMaker ETL, on-demand/Spot-aware training, JSON→CSV logging for QuickSight, robust JWT/KMS/IAM controls, and full IaC via Serverless. Impact: cut query spend, fixed training failures, unified CRUD flows, unlocked live analytics, and hardened SOC2/HIPAA data security.
Built a HIPAA-ready medical transcription platform. Goals: automate transcription of clinical audio, store and secure patient data. Solutions: multiple AWS microservices (appointments, organizations, users, payments) deployed via Serverless and CI/CD. Transcription uses Fargate to run Kubernetes jobs, triggered by Lambdas. DynamoDB tables use KMS encryption and tagging. Impact: automated infrastructure deployment, strong role-based security, and compliance practices that make the platform scalable and safe for PHI.
Bachelor of Engineering (BEng) in Computer engineering