About the job
Podium Automation is a pioneering startup dedicated to transforming the industrial control panel manufacturing landscape through innovative software-driven design and automated fabrication. Our mission is to revolutionize the industrial supply chain, dramatically reducing lead times for essential electrical equipment from several months to mere days. With robust backing from a16z’s American Dynamism fund, SV Angel, and Banter Capital, we are rapidly expanding in New York City.
We are on the lookout for a Staff Software Engineer who is passionate about creating cutting-edge technology in the built environment. You will take ownership of our component intelligence platform, which serves as the foundation for instantaneous and precise panel design.
The Challenges You Will Tackle
Industrial control panels are composed of numerous components including contactors, terminal blocks, PLCs, switches, and more, each with intricate, structured data like terminal semantics, electrical ratings, spatial information, and certifications. Unfortunately, much of this vital data is not readily accessible in machine-readable formats; instead, it's hidden within complex and inconsistent sources such as PDFs, user manuals, datasheets, STEP files, and diagrams. Manual data structuring is not scalable, and that's where you come in.
Your mission will be to address this issue from the ground up by designing and developing systems that efficiently extract, validate, and deliver reliable information from these multifaceted data sources.
Your Responsibilities
Technical Leadership: Take charge of the technical roadmap and enhance our proprietary data model for industrial devices.
Data Extraction Pipeline: Design and implement extraction pipelines that derive structured data from PDFs, datasheets, user manuals, STEP files, images, and manufacturer APIs. Your solutions may incorporate specialized parsers and validators, established tools such as OCR libraries, machine learning techniques, or a combination of these , you'll have the autonomy to choose the most effective approach.
Ongoing Optimization: Extraction is merely the beginning. We continuously iterate and refine component data, gradually building trust in it over time. You will implement confidence scoring, human-in-the-loop review processes, and rollout strategies, presenting device data with varying levels of accuracy, completeness, and usability.
Collaborative Engagement: Work closely with electrical and process engineers to ascertain data requirements and ...
