Software Developer in Test - Spatial Intelligence
Team: Perception
Location: Barcelona, Catalonia
Commitment: Employee (100-80%)
Workplace Type: hybrid
Your contributions
- Evolve our replay, simulation-in-the-loop, and hardware-in-the-loop testing capabilities to validate perception, SLAM, and world model systems across diverse real-world scenarios while reducing the sim-to-real gap.
- Drive the test automation journey within the Spatial Intelligence team by building validation frameworks that enable fast and high-quality software releases.
- Take ownership of the overall quality of the Spatial Intelligence stack by defining quality standards, regression criteria, and validation gates that prevent issues from reaching the field.
- Proactively improve system diagnosability and debugging workflows to reduce the time spent investigating and resolving field issues, enabling faster recovery and continuous reliability improvements
- Contribute to the continuous improvement of our CI/CD pipelines and dataset infrastructure to ensure scalable validation of data-driven and learning-based spatial intelligence components.
- Help maintain and extend ANYbotics’ testing facilities and occasionally participate in structured validation and data collection campaigns to strengthen our scenario catalog.
You profile
- Excellent knowledge of software quality assurance and automated testing of complex, distributed systems.
- Excellent programming skills in C++ and Python with a strong understanding of testable software architecture and clean code design.
- Strong experience designing replay-based or large dataset-driven validation pipelines for learning-based or data-centric systems.
- Strong ability to analyze complex system-level failures and improve observability, diagnosability, and debugging workflows to reduce time-to-resolution.
- Good familiarity with Linux development environments, Git workflows, and CI/CD pipelines.
- Good experience with issue tracking and test management tools, and defining regression and quality metrics.
- Engineering or science degree with a focus on computer science, robotics, or a related field.
Bonus points
- Experience testing robotic perception, localization, or SLAM systems in simulation and real-world setups.
- Experience working with ROS2, robotics sensor systems (cameras, lidars, IMUs) and their common failure modes.
- Experience with robotic simulators (e.g., Gazebo, Isaac Sim) and their limitations in representing real-world sensor behavior.
- Experience validating machine learning models or working with ML evaluation frameworks.
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