Embedded Perception Engineer
Tasks
- Apply quantization and pruning for model optimization
- Build end to end perception pipelines for operational systems
- Define metrics and evaluation frameworks for system health
- Deploy models using NVIDIA Triton Inference Server
- Design train and optimize perception models
- Develop and validate sensor drivers for data pipelines
- Develop object detection classification and tracking systems
- Fuse multi modal sensor data into unified outputs
- Integrate perception outputs into autonomy stacks
- Investigate perception failures and drive resolution across teams
- Monitor deployed system health and performance
- Optimize inference for latency and throughput on edge hardware
- Translate field challenges into engineering solutions
- Troubleshoot perception performance in operational environments
Perks/Benefits
- 401k matching
- Dental insurance
- Global Entry
- Health and wellness stipend
- Health insurance
- Life insurance
- Paid parental leave
- Unlimited PTO
- Vision insurance
- Work from home stipend
Skills/Tech-stack
C++ | CLIP | CUDA | Computer Vision | Deep learning | Edge AI | FPGA | Image classification | Inference Server | Linux | Multimodal Learning | NVIDIA Jetson | NVIDIA Triton | NVIDIA Triton Inference | NVIDIA Triton Inference Server | ONNX | ONNX Runtime | Object Detection | Pruning | PyTorch | Python | Quantization | ROS2 | Real Time | Real-time Inference | Real-time Systems | SAM | Sensor fusion | TensorFlow | TensorRT | Time Systems | Tracking | Triton Inference Server | Vision Transformers
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
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