13 set - Bardi
Oversonic
We are looking for a hands-on Robotics Software Engineer to join our Navigation Team.
This is an operational role, not a research one: our robots are already deployed in factories, and we need someone to solve the complex engineering problems that only appear in production.
You will own the software platform beneath our navigation stack.
By collaborating across the Software, Hardware, and Customer Support teams, you will ensure our system becomes increasingly robust—taking end-to-end ownership from debugging code to troubleshooting the physical robot on the factory floor.
Key Responsibilities
Maintain & Optimize:
Debug and refactor existing ROS/ROS 2 C++ and Python codebases rather than building from scratch.
Hands-on Hardware:
Configure hardware, calibrate sensors (LiDAR, IMU, cameras), and test physical robots.
Testing & Tuning:
Measure the robot's performance against tech specs and tune SLAM, localization, and path-planning for dynamic environments.
Field Support & Deployment:
Troubleshoot production issues, validate bug fixes on hardware, and provide technical assistance for deployed robots.
Requirements
Degree in Robotics, Computer Science, Automation Engineering, or a related field.
Real-world experience deploying, testing,
and maintaining autonomous robot navigation systems.
Strong C++ and Python skills with a knack for debugging existing code.
Solid practical ROS/ROS 2 experience, especially the navigation stack (Nav2).
Ability to diagnose complex hardware/software interactions and troubleshoot sensors (LiDAR, RGB-D cameras, IMUs).
Familiarity with IoT/streaming protocols (MQTT, NATS, WebRTC).
Proactive team player with transparent approach, willing to help others and continuously improve daily operations.
Willingness to travel occasionally to customer sites for on-site troubleshooting.
Full professional proficiency in English.
Nice to Have
Experience with industrial robots, AMRs (Autonomous Mobile Robots), or AGVs, including the commissioning of automation systems and industrial tools.
Experience with modern software practices: Docker, Kubernetes, CI/CD pipelines.
Experience with robotic fleets management systems
Familiarity with AI/ML and Deep/Reinforcement Learning techniques applied to robotics.
Contract:
Full-time, permanent.
Flexibility:
A flexible start time (1.5-hour window).
Hybrid Work:
Opportunity to work from home one day per week.
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