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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Software Engineer - **Company:** Monumental - **Location:** Netherlands - **Contract:** Internship / Graduate position - **Skills:** C (Programming Language), Computer Vision, Unit Testing, C++ (Programming Language), Python (Programming Language), Kinematics, Motion Planning, Software Construction, Software Engineering, TypeScript, Visual Systems, Rust (Programming Language), Jupyter Notebook, Deep Learning, Git, Deployment Automation - **Published:** September 5, 2026 - **Apply:** https://startup.jobs/software-engineer-computer-vision-monumental-8369634 ## About the Role * Industry experience building and deploying 3D vision systems into production. * Deep understanding of, and hands-on experience with, multiple hardware sensor systems - LiDARs, IMUs, and (depth) cameras. * Experience developing, implementing, and testing mapping, localisation and state estimation algorithms such as (VI-)SLAM, VIO, ICP, and Kalman filters. * Ideally, some experience with real-time, deep-learning-based computer vision - e.g. multi-object tracking systems. * Proven software engineering experience in C, C++, Python, Rust, or comparable languages - beyond doing things in a Jupyter notebook. * Software engineering best practices: git for version control, unit testing, automated deployment. * A strong bias for action and output. We're not a research organisation - we ship frequently and iterate fast. * A strong sense of ownership and motivation., If you don't meet all the qualifications here but are excited about Monumental and feel you'd still be able to help us solve difficult problems, do get in touch. We welcome generalists who focus on outcomes and are eager to learn on the job. ## Description We're looking for engineers with deep knowledge of software and modern 3D computer vision. We're building an operating system to make on-site construction possible with robotics. Our software stack allows us to do everything from 3D reconstruction of the construction site (through photogrammetry), design of custom wall structures, training and deploying vision algorithms, supply chain, path planning, and robot controls and kinematics. Some of the challenges we're solving with computer vision: * We make 3D reconstructions of construction sites that let us match the architect's (ideal) drawings to the real world. These reconstructions are made in challenging conditions - low or harsh light, limited space - by operators who aren't computer vision experts, and we need a fast turnaround so our robots can get building immediately. * Our robots place bricks and mortar with sub-millimetre accuracy in a global reference frame. These are higher accuracy requirements than autonomous driving, which means we ask more of our sensors - an off-the-shelf RealSense camera doesn't cut it. * Our robots aren't always on stable ground. Sometimes we build a canal wall from a boat, or work off a wobbly scaffold. That means compensating live, so we can still build a beautiful building. You can read about how we control robots with TypeScript in this post by our CTO, Sebastiaan. If you're new to robotics, you might enjoy reading Bouke's blog post on his experience joining Monumental as a software engineer. What you'll do * Developing algorithms for localisation, mapping, calibration, and state estimation using state-of-the-art techniques, allowing us to drive our autonomous vehicles in the ever-changing environment of a construction site. * Building the continuous localisation system for our robots, combining camera, depth, and IMU data to keep track of where the robot is at all times. * Designing and building vision systems that understand the construction site: spec the right cameras and sensors, train models that judge the quality of bricks and mortar, or recognise construction objects. * Implementing robust, production-level code that brings your algorithms to life. You own your projects from start to finish and don't approach problems like a researcher who hands a Jupyter notebook to a separate software engineering team. * Measuring the performance of our sensing system on a continuous basis, characterising the sources of error and performing root cause analysis - even when the robot is out on a construction site and you don't have direct physical access to it. ## Related Videos - [Robots are coming into the wild! 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