模型部署与推理优化工程师
Tasks
- Adapt inference engine to target hardware
- Automate model packaging remote push on device loading and validation
- Build one click model deployment toolchain
- Create inference performance benchmark suite
- Deploy VLA models to edge devices
- Implement hot model updates and version rollback
- Improve inference performance
- Monitor latency accuracy and resource usage after updates
- Optimize models with quantization, pruning, distillation
- Research and apply efficient inference frameworks and optimization algorithms
Perks/Benefits
- N/A
Skills/Tech-stack
C++ | Edge inference | Inference Performance | Inference Performance Optimization | Model Distillation | Model Pruning | Model Quantization | ONNX Runtime | Performance optimization | Python | TensorRT
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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