Software Developer for Sensor Data Fusion
Germany, Berlin, BerlinLocalization / Sensor Fusion
Are you interested in being part of a team of experts launching a scalable autonomous vehicle in Germany?
If yes, we’d love to hear from you!
The type of challenges we currently offer
We are looking for you as an SOFTWARE DEVELOPER FOR SENSOR DATA FUSION
What You’ll Do
- Help develop a single rich map by merging various sensor detections
- Help build a communication channel between our Perception and Decision teams
- Create a robust fusion pipeline by analysing and implementing the state-of-the-art correspondence techniques
- Independently evaluate all the fusion stages
- Code and test your approach on public and in-house data sets (challenging our current set up is welcome!)
Please send applications to email@example.com
WHO WE ARE
We are Motor Ai, located in Berlin developing an autonomous driving system based on cognitive neuroscience and groundbreaking German research. Motor Ai is Germany's only start-up on the road to Level 5 autonomous driving. This summer in 2021 Germany became the first country in the world to pass a law allowing Level 4 autonomy nationally (car is almost fully autonomous, safety driver can be remote). The German law will become the blueprint for future EU legislation.
Our ambition is to be the first to roll out an autonomous driving product. Join us in making this a reality, in shaping and guiding the future of driving!
We offer an innovative, creative, and intellectually stimulating work
environment and the chance to take full ownership of your code,
following it from back-of-the-napkin idea to real world product.
A) What you have as a SOFTWARE DEVELOPER FOR SENSOR DATA FUSION
- Previous hands-on experience with data fusion of exteroceptive sensors
- A strong expertise in sensor behaviour in various environments and weather conditions (lidar, radar and cameras a plus!)
- A high-level understanding of the camera projection matrices
- Comprehensive knowledge of computer vision and various optimization methods
- Experience with deep learning frameworks like Tensorflow or Pytorch
- Excellent coding skills in Python and C++
- Experience in deep learning frameworks (e.g. Tensorflow or Pytorch)
- Previous hands-on experience with ROS2 as a middle-ware, as well as PLC and OpenCV libraries
- Good English proficiency
B) Nice to have
- Knowledge of occupancy grid generation and scene understanding via 3D maps
- Knowledge in performing object and ego state estimation based on 3D maps