- Location
- Austin, TX
- Workplace
- Hybrid
- Type
- Full-time
- Department
- Engineering
- Seniority
- Senior
- Source
- Lever
Description
About Circuit
Circuit is the AI execution layer for the physical economy.
Industrial and manufacturing enterprises run on expertise: the hard-won knowledge of how complex products are engineered, configured, sold, and supported. That expertise is scarce, slow to transfer, and walking out the door as a generation of experts retires. It lives in PDFs, spreadsheets, and the heads of a few people, and the hardest technical decisions wait on whoever happens to know.
Circuit puts expert judgment in everyone's hands. We capture how the best people make critical technical decisions and turn it into agents that do the judgment-heavy work, so anyone, regardless of skill level, can make the right call, from quote to install and support, with the accuracy these environments demand.
Circuit is built by operators. Our leadership team has built and scaled real industrial companies, and we are already live in production with category-leading manufacturers. We are not bolting AI onto an old playbook. We are building the layer that runs the last mile of how the physical economy executes.
The Role
As a Staff Engineer, Applied ML at Circuit, you’ll join Product Engineering and build the machine learning capabilities that power our product. You’ll work closely with Forward Deployed Engineers (FDEs), Product Engineers, and directly with design customers to understand real-world challenges and turn them into robust, scalable solutions. A core part of your role is recognizing where a customer need points to a broader product capability, then building it to work across customers and use cases.
This is a hands-on engineering role focused on solving current product and customer problems. You’ll use advances in ML where they help, exercise judgment about what is ready to ship, and own solutions end to end, with attention to accuracy, reliability, latency, and cost. Success means delivering capabilities that make Circuit’s product more useful, reliable, and broadly applicable.
You’ll draw primarily on LLMs, alongside traditional NNs and statistical models, choosing and combining approaches based on the problem. Your work will span understanding customer use cases and how users interact with the product, data and process modeling, understanding what exists today and how to build on it, evaluation, production implementation, and, where it pays off, model training and fine-tuning. Most importantly, you’ll work end to end with our design customers, building solutions for them. Beyond individual features, you’ll help build shared capabilities such as Circuit’s evaluation framework, improving how we measure quality and catch regressions across the product. As priorities evolve, you’ll apply your engineering judgment wherever it can make the greatest impact.
Product Engineering builds the core platform and works directly with customers and design partners. Our FDE teams own solutions architecture and technical demonstrations. You’ll work alongside them on what gets built, and partner with Core ML engineers when a customer problem calls for deeper work on our document models or the agent loop. Your teammates range from full-stack engineers to applied ML researchers.
What Is in Production Today
Our core product includes a long-running agent loop written in Go. Frontier model APIs drive the loop, while specialized tools handle retrieval, extraction, and agent execution. These tools let us solve industrial problems that general-purpose agent harnesses struggle with.
We use a combination of open-source and internally fine-tuned models, particularly vision-language models (VLMs), hosted on KServe. Our customer data includes technical documents, high-resolution blueprints, raster images, vector geometry, CAD, and structured data.