Lead Software Engineer - Backend and Optimisation

Benchmark Construction Technology Corp

About The Position

You'll build the backend APIs and mathematical core of our design engine, developing optimisation models, geometric algorithms, and simulation systems that translate extracted plan information into physically valid, optimised 3D building structures — all while capturing the real-world constraints of residential construction and serving these models to our applications. Your work will power the engine that turns drawings into buildable designs.

Requirements

6+ years of experience developing mathematical or optimization systems in production environments
Expert Python programming skills with experience building complex numerical or algorithmic systems
Strong background in operations research, constrained optimization, linear programming, or mixed-integer programming
Strong understanding of algorithm design, computational complexity, and performance optimization
Experience implementing or working with computational geometry algorithms
Comfortable working in Linux environments and deploying production systems

Nice To Haves

Experience with OR solvers (Gurobi, CPLEX, SCIP, OR-Tools)
Background in computational geometry, geometric modeling, or spatial algorithms
Experience building large-scale optimization systems
Familiarity with performance optimization in numerical or simulation workloads
Familiarity with the construction, CAD, or manufacturing domains
High agency: you take ownership of difficult systems and drive them to production
You enjoy translating messy real-world rules into clean mathematical formulations
You care deeply about performance, determinism, and correctness
You are comfortable operating independently in a fast-paced engineering environment
You communicate clearly and collaborate well with engineers across disciplines

Responsibilities

Build APIs and services to provide conduction design models to frontend applications using Python and FastAPI.
Design and implement optimization models using operations research techniques including constrained programming, linear programming, and mixed-integer programming (MIP)
Develop computational geometry systems that convert plan-derived data into structured 3D building representations
Build simulation and constraint systems that model real-world construction rules, structural relationships, and material layouts
Develop production-grade Python systems that solve large-scale optimization and geometric problems
Improve performance and scalability of heavy mathematical workloads through algorithm design, solver tuning, and profiling
Work closely with ML engineers and platform engineers to integrate optimization systems into the broader plan ingestion and design pipeline
Ensure mathematical systems are reliable, testable, maintainable, and production-ready