Data Scientist (Math and 3D Geometry)

About the Company

InCommon is hiring on behalf of a US-based construction robotics company building software and robotic systems to automate home construction. Their platform converts architectural plans into precise digital models and robot-ready instructions using computer vision, optimization, and computational geometry. Founded in 2020 and headquartered in North Carolina, the company operates at the intersection of AI, math, and robotics, with the goal of making home construction faster, more scalable, and more reliable.

What you’ll do

Develop and optimize the “heavy math” engine that converts plan-derived inputs into a precise 3D representation of how a house would actually be built, using geometry + optimization at scale.

Responsibilities

• Build constrained optimization and simulation models (LP/MIP/CP) for structure generation
• Implement robust 3D computational geometry modules and validation checks
• Performance engineer C++ code paths for large, complex plans (runtime and memory)
• Extend model coverage for edge cases and diverse home designs while maintaining correctness

Must-haves

• Operations Research depth (LP, MIP, constraint programming), strong modeling instincts
• C++ with performance engineering experience
• Strong computational geometry background (2D/3D)
• Ability to reason about correctness, constraints, and failure modes

Nice-to-haves

• Experience with OR-Tools / Gurobi / CPLEX / CBC (or similar)
• Familiarity with building structures, framing logic, or AEC tooling
• HPC mindset (profiling, vectorization, parallelism where appropriate)