Lead ML Engineer - Computer Vision

About the role

You’ll own and expand our AI-enabled plan ingestion pipeline—from raw PDFs to clean, dependable outputs that power takeoff, design, and downstream automation.

What you'll do

• Architect, build, and deploy ML systems for object detection, segmentation, document understanding, and information extraction from complex building plans
• Drive R&D across computer vision and/or NLP as applied to construction documents and related data
• Develop multi-modal approaches that combine vision with language features for document analysis (LLMs/NLP). Familiarity with different RAG methods is a plus
• Mentor junior engineers and help raise the bar on execution, code quality, and decision-making
• Ensure systems are reliable, maintainable, testable, and observable in production

Qualifications

• 8+ years of experience in Machine Learning Engineering, with deep focus in computer vision
• Expert Python skills, with strong experience in PyTorch and FastAPI
• Proven work with segmentation models, detection frameworks, and OCR/document pipelines
• Strong image processing fundamentals (OpenCV, geometric transforms, preprocessing, etc.)
• Comfortable in Linux; hands-on with Docker/containerization for deployment
• Experience building and maintaining MLops infrastructure (e.g., ClearML, MLflow)
• Ability to design scalable, high-performance ML systems (not just prototypes)
• Strong problem-solving ability and comfort operating independently in a fast-paced environment

What Makes You a Great Fit

• High agency: you ship, iterate, and fix what’s broken—without waiting for permission
• You’ve delivered ML systems end-to-end in production (data → model → deployment → iteration)
• You’re a strong engineer who cares about getting better—trajectory matters here
• You communicate clearly, especially with a remote and cross-cultural team
• You’re gritty and genuinely enjoy solving hard problems

Bonus Points

• Experience building systems for document reading / understanding
• Ambitious, driven, and opinionated about quality and craft
• Experience with deep learning inference frameworks (e.g., TensorRT, PyTorch compile) and optimizing inference performance
• You keep up with current ML/AI developments and can apply them pragmatically

What We Offer

• Competitive salary + meaningful equity
• Comprehensive benefits (health, dental, vision)
• Professional development budget (courses, conferences, research exploration)
• Real-world ML problems with direct impact
• High growth potential