Senior Computer Vision Engineer

R3 Robotics

Luxembourg

Your Role

As a Senior Computer Vision Engineer, you will contribute to the core software powering our automated battery disassembly lines: the perception that lets our robots understand and act on what they see. You will own computer vision modules end-to-end, from prototyping and experimentation through to production-grade deployment, working directly with robots, 3D sensors, and real production data. You will shape the perception stack from an early stage, push the state of the art where the status quo hits its limits, and bring software engineering best practices to a small, fast-moving team. This position suits an experienced engineer who excels technically but also wants to see their work move “not only bits but atoms” and make a real difference in production.

Your Responsibilities

Design and implement computer vision pipelines for automated battery disassembly, delivering both proof-of-concept prototypes for experiments and production-quality code for the customer-facing solution. Core challenges include:
- Object detection, classification, and 6D localization;
- Segmentation, tracking, and counting;
- 3D reconstruction of objects and post-processing of 3D scans;
- Camera calibration, applying robotics knowledge and 3D transformations to relate sensor data to the robot workspace;
- Closed-loop perception-control for robot manipulation.
Work with industrial machine vision cameras (RGB and 3D), challenging the limits of what data can be acquired and extracted from them;
Implement both classical and learning-based computer vision techniques on real-time platforms, aiming for effective and reliable utilization;
Take prototypes to production with guaranteed quality, implementing tests and documentation for reproducibility and reliability;
Navigate the trade-offs between technical complexity and getting things to work: favour simple methods to solve complex tasks, but push the state of the art when needed;
Own your tasks end-to-end, including data collection and labelling processes, testing, and integration through to the finished product;
Perform root cause analysis and demonstrate strong debugging skills when things fail;
Bring software engineering best practices to the team and contribute to the technical growth of the vision team;
Work with a high degree of independence: own the planning of your specific scope when required, produce design documents, and follow an agile software development process, including creating test plans and validation plans;
Operate effectively within cross-functional teams (mechanical, electrical, and software), communicating clearly to a wider audience what is needed and why. We do not work in isolation.

Your profile

Deep understanding of modern computer vision, covering both machine learning and classical methods. A Master’s degree (or higher) in Computer Science, Applied Mathematics, Robotics, or another STEM field is preferred;
A minimum of 4–5 years of experience in a similar position, with at least one relevant experience in the machine manufacturing or industrial automation industry;
A background in robotics or other areas involving 3D vision is strongly preferred;
Strong mathematical foundation; linear algebra and vector operations area must;
Proventrack recordof developing production-grade software in Python and C++ (or similar), including experience with deep-learning frameworks such as PyTorchor TensorFlow and libraries such as OpenCV;
Hands-on experience developing, training, and testing deep-learning algorithms for detection, classification, segmentation, and tracking, including filtering and augmenting large image datasets;
Experience with optical, image-sensor, or camera calibration and the associated computer vision principles is a plus;
Familiarity with collaborative software development: Git, testing, and CI/CD for code deployment;
Strong bias for action and output. We are not a research organization: we embrace fast iteration loops and quick feedback; “Fail fast, recover faster.”
Strong sense of ownership, autonomy, and motivation, including ownership of failures: ability to perform root cause analysis and drive issues to resolution.