Principal Applied Scientist - Robotics
Tasks
- Apply reinforcement learning and action conditioned planning
- Build multimodal AI systems
- Define robotics perception and embodied ai roadmap
- Design dataset strategy and evaluation protocols
- Develop real-time perception models
- Establish code review testing and delivery readiness
- Execute data pipelines and deployment integration
- Integrate ai capabilities with robotics software and hardware
- Lead model training fine tuning and optimization
- Lead multi sensor fusion research
- Mentor scientists and engineers
- Monitor production metrics and feedback loops
- Perform root cause analysis for complex integration issues
- Prototype ai capabilities for robotic systems
Perks/Benefits
- N/A
Skills/Tech-stack
API Integration | Action Conditioned Planning | Activity Recognition | Artificial Intelligence | C++ | Computer Vision | Data labeling | Dataset design | Decision Making | Fine Tuning | Inference Optimization | Localization | Machine Learning | Model Fine-tuning | Model Optimization | Model Training | Multimodal Learning | Object Detection | Object Tracking | Planning | PyTorch | Python | ROS | Real Time | Real-time signal processing | Reinforcement Learning | Robotics | Scene Understanding | Sensor fusion | Signal Processing | Simulation | State Estimation | Synthetic data
Education
Bachelor of Engineering | Bachelor of Science | Doctorate | Master of Science | PhD
Regions
Countries
States
Cities
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