Senior Computer Vision Engineer- US

About Us:

STACK is a leading provider of cloud-based construction estimating and takeoff software solutions, committed to helping businesses transform through innovative solutions. We pride ourselves on fostering a collaborative, dynamic environment where team members have the opportunity to grow and make a real impact.
About the Role:

We are hiring a Senior Computer Vision Engineer to improve our computer vision system for construction documents. This role focuses on detection and segmentation quality, geometric accuracy, and production-grade pipelines that work reliably with messy real-world PDFs and drawings.
What You’ll Do:

- Design, build, and improve end-to-end detection and segmentation pipelines for document images.

- Improve document ingestion for PDFs and other unstructured files, including parsing, rendering, and handling of multi-page and multi-view content.

- Increase model accuracy, boundary and geometric quality, and overall reliability of predictions for downstream use.

- Integrate modern detection and segmentation models into production workflows and build the post-processing that turns model output into structured, usable geometry.

- Define evaluation metrics, investigate failure cases, and drive continuous quality improvements.

- Optimize latency, reliability, and cost across the inference and post-processing stack.

- Own training infrastructure, dataset curation, annotation quality, and continuous-improvement loops.

- Make architectural decisions and own system quality end to end.

What You Bring:

- 5+ years experience building computer vision systems: detection, segmentation, or structured geometry extraction, used high volume in production.

- Experience working with messy, real-world image data or large unstructured visual datasets.

- Strong understanding of detection and segmentation tradeoffs, including model architecture choices, training data design, and post-processing.

- Ability to measure system performance with evaluation, testing, and production metrics.

- Ability to explain failure modes clearly and improve systems through debugging, dataset work, and iteration.

- Experience with multimodal models (vision-language models, document AI systems)

- Understanding of grounding — linking model outputs to source data or coordinates

- Backend engineering experience, including APIs, async processing, and scalable GPU services.

Additional Preferred Qualifications:

- Experience with polygon or mask post-processing, geometric regularization, or CAD-style structured output.

- Experience with layout-aware document processing, PDF vector extraction, or combining raster and vector signals.

- Background in document-heavy CV domains such as construction, real estate, medical imaging, geospatial, or similar workflows.

- Experience optimizing inference cost and latency at scale.

- Familiarity with open-source detection / segmentation ecosystems, training infrastructure, or model serving.

What Success Looks Like:

- Accurate, geometrically correct predictions suitable for downstream measurement, and analysis use.

- Fast, reliable inference across large and messy real-world document sets.

- Clear quality metrics and a repeatable improvement loop.

- Systems that perform consistently under real-world production constraints.

What This Role is Not:

- Not a model-training-only role. You'll own data, training, post-processing, and serving.

- Not a research-only role.

- Not a plug-and-play CV tools environment.

Why Join STACK?

- Opportunity to work in a fast-paced, growth-oriented, remote-first environment.

- Async-friendly environment with a focus on ownership and deep work.

- Be part of a dynamic, supportive team where your contributions are valued.

At STACK, our values shape how we work, collaborate, and serve our customers:

- Radical Honesty: Communicate directly, respectfully, and transparently—even when conversations are difficult. Give and receive feedback with care.

- Cus