Lead Edge AI Engineer
Tasks
- Collaborate with firmware and mobile teams
- Deploy computer vision algorithms to embedded android
- Develop multi-task learning models
- Develop video action recognition systems
- Implement safety mechanisms for system stability
- Integrate algorithms with qualcomm snpe and qnn sdk
- Integrate signals for model decision making
- Manage thermal constraints
- Minimize model switching latency
- Optimize models for edge resource constraints
- Reconfigure model graph during runtime
- Reduce power consumption
- Refine hydranet architecture models
Perks/Benefits
- Customized benefits
- Flexwork arrangements
- Medical insurance
- Parental leave
- Term life insurance
- Wellbeing programs
Skills/Tech-stack
3D Reconstruction | Action Recognition | Android Development | Camera localization | Computer Vision | Conditional Computation | DSP Optimization | Dynamic Graph Execution | Embedded Systems | GPS | Graph Execution | Graph Splitting | Hexagon DSP | IMU | Low-level system | Low-level system software | Magnetometer | Memory bandwidth | Model Optimization | Motion estimation | Multi-task Learning | Power Management | Pruning | PyTorch | Python | QNN SDK | Qualcomm Hexagon | Qualcomm Hexagon DSP | Qualcomm QNN | Qualcomm QNN SDK | Qualcomm SNPE | Quantization | Sensor fusion | System Software | Thermal Management | Video Action Recognition
Education
Roles
AI Engineer | Data Scientist | Edge AI Engineer | Engineer | Lead | Lead Data | Lead Data Scientist | Scientist
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