This role involves designing and deploying robust state estimation algorithms that enable robots to understand their position in real-time dynamic environments
Job Summary
This role involves designing and deploying robust state estimation algorithms that enable robots to understand their position in real-time dynamic environments.
Candidates will leverage modern machine learning approaches alongside classical geometric techniques to enhance perception system performance on resource-constrained hardware.
The successful applicant will own the full pipeline from research prototyping through production deployment, working directly with sensors and robotic platforms like Sprout.
Matching Summary
This role involves designing and deploying robust state estimation algorithms that enable robots to understand their position in real-time dynamic environments.
Salary
Not specified; Not specified; Not specified
Skills & Requirements
Must-have
Visual Inertial Odometry algorithm design
Multi-sensor fusion pipeline development
Embedded hardware optimization for robotics
Real-time state estimation implementation
Sensor calibration and benchmarking infrastructure
Nice-to-have
Modern deep learning perception techniques
Experience with neural odometry methods
Collaboration with hardware and controls teams
Prototyping in physical environments
Combining learned representations with geometry
Key Requirements
Strong foundation in VIO and sensor fusion
Practical experience optimizing algorithms for embedded platforms
Familiarity with modern deep learning in perception