Lead Principal Applied Scientist - Robotics
Tasks
- Apply reinforcement learning and action conditioned planning
- Build perception pipelines for object detection tracking and scene understanding
- Conduct root cause analysis for systems integration issues
- Define robotics perception strategy
- Design dataset and labeling strategies
- Develop real time signal processing models
- Establish code review testing and delivery best practices
- Execute data pipelines experimentation evaluation deployment
- Integrate AI capabilities into robotic systems
- Lead multi sensor fusion research
- Mentor scientists and engineers
- Monitor production performance with operational metrics
- Perform model training fine tuning optimization and inference
- Prototype multimodal AI systems
Perks/Benefits
- N/A
Skills/Tech-stack
Action Conditioned Planning | Activity Recognition | Artificial Intelligence | C++ | Computer Vision | Decision Making | Localization | Machine Learning | Multimodal AI | Object Detection | Planning | PyTorch | Python | ROS | Real Time | Real-time signal processing | Reinforcement Learning | Robotics | Scene Understanding | Sensor fusion | Signal Processing | State Estimation | Tracking
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
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