In this role, you will...
- Contribute to the ongoing development of new architecture based on new, state of the art ML research
- Investigate, prototype and train/evaluate networks for solving data association problems ie: track-detection matching, using geometric and embedded features
- Investigate, prototype and train / evaluate networks for solving recursive and / or moving window filtering / estimation problems for non-stationary non-Gaussian noise
- Investigate, prototype and train / evaluate networks for solving dynamic occupancy estimation problems with and without agent/shape assumptions
- Investigate, prototype and train / evaluate networks for solving causal / recursive multi-target multi-modal tracking problem
Qualifications
- 7+ years of experience with programming and algorithm design
- Fluency in C++ and Python
- Experience with modern computer vision techniques like Transformers
- Experience with tracking techniques like data association and state estimation
- Demonstrated ability to create realtime systems that solve difficult perception tasks
- Strong mathematical skills and understanding of probabilistic techniques
Bonus Qualifications
- Bachelor's, Master's or PhD in computer science, statistics, mathematics or related field
- Publications in your field (CVPR, ICCV, RSS, ICRA preferred)
- Experience with building perception pipelines that work with real data in rapidly changing and uncertain environments.
- Experience with realtime sensor fusion (e.g. LiDAR, camera, radar)
- Experience with data representations like pointclouds, meshes, voxel-representation, pixel-domain, etc.
- Experience with nonlinear non Gaussian multi hypotheses tracking
- Experience with weighted nonlinear least square estimation like GTSAM
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