Founding Engineer (Applied AI)

Department: Engineering

Location: San Francisco

Employment Type: FullTime

About the Role

This is a founding engineering role at an early-stage AI startup transforming the construction pre-construction workflow through automated blueprint understanding and cost estimation. You'll own the intelligence layer — advancing computer vision and AI systems from research to reliable, shipped products that real users depend on. It's a high-impact position on a small, fast-moving team where your work directly shapes the core product.

What You'll Do

• Drive the intelligence layer of the product, focusing on CV/ML systems rather than application-layer work.

• Apply cutting-edge computer vision models, LLMs, and AI systems to real construction workflows.

• Ship initial prototypes quickly, then iterate and improve based on direct user feedback.

• Coordinate and compose multiple ML models into coherent, production-ready pipelines.

• Roll up your sleeves for hands-on, ground-level work — this team embraces "schlep" as part of building early-stage products.

What We're Looking For

• Proven 0-to-1 builder with AI systems shipped to production.

• Strong applied ML experience, including machine learning, deep learning, and computer vision (object detection a plus).

• Proficient in Python and comfortable working across the ML stack.

• Growth mindset — values trajectory and continuous learning over prior pedigree.

• Communicates with empathy and honesty; proactively flags what's working and what isn't.

• Comfortable with ambiguity and repetitive foundational work common at early-stage startups.

• US citizenship required (visa sponsorship is not available).

• Bonus: background in construction or estimating.

• Bonus: prior experience founding or contributing early to a product that attracted real users or paying customers.

Compensation & Benefits

Base salary range: $120,000 – $180,000 USD annually. Equity participation expected at the founding engineer level. No visa sponsorship available.

Location

On-site, full-time in San Francisco, California, USA. Candidates must be based in SF or willing to relocate.