Anton S.
Software Engineer
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Anton Mark S. is a seasoned Software Engineer and licensed Electronics Engineer (ECE & ECT) with over five years of professional experience across software development, machine learning, and analog IC design, focusing on the electronics and semiconductor industries. At SnapMagic, he engineered a robust circuit auto-wiring system and developed AI-powered schematic component classifiers using Python, Java, and advanced AI models, automating CAD workflows and component identification in electronic design. Previously at Analog Devices, Anton Mark S. reduced test cycle times by building ML-based optimization models and automated circuit-to-simulation pipelines utilizing deep neural networks and NLP. His expertise extends to full-stack development, deployment (Heroku, Cloudflare), and verification environments involving C++, Verilog, and Linux, directly impacting production efficiency and engineering quality.
Experience
Software Engineer
SnapMagic · 2023 — PresentDeveloped a circuit auto-wiring system utilizing matrix operations and pathfinding algorithms, streamlining a manual CAD workflow. Constructed an AI-powered schematic component classifier using GPT-4 Vision for automated identification of electronic components. Trained a custom object detection model for schematic symbol recognition with YOLOv8 and Roboflow, enhancing the accuracy of CAD tools. Created and supported full-stack features including front-end UI and back-end services using Python, Java, and C++, linked through REST APIs. Produced detailed unit tests and automated regression suites to improve deployment confidence and decrease bug escape rate. Oversaw deployments and monitoring with Heroku, Cloudflare, and New Relic to ensureMachine Learning Engineer
Analog Devices · 2021 — 2023Improved the tester cycle time for ADC/DAC test programs through the development of ML-driven optimization models, enhancing production throughput. Established a Schematic-to-Behavioral modeling pipeline with deep neural networks, facilitating the conversion of circuit schematics into simulation-ready models. Developed an NLP-based error parser that efficiently classified and routed test log errors, significantly reducing manual triage duration. Created a sentiment-based text classification system alongside a grammar verification tool for internal documentation quality, while leading an internal Machine Learning community of practice to promote ML adoption among engineers.Analog IC Design Engineer
Analog Devices · 2020 — 2021Conducted analysis of circuits and schematics for analog IC designs, verifying connectivity and functionality for automated test equipment. Streamlined test creation workflows through automation with Python, minimizing manual effort and enhancing test coverage. Wrote verification scripts in C/C++, Verilog, and SystemVerilog within a Linux-based development environment.
Skills & Expertise
Education
- Bachelor of Science in Electronics EngineeringHoly Angel University · — — 2019