Edge AI Engineer
Tasks
- Apply model compression techniques
- Apply model quantization
- Build inference runtimes
- Build privacy preserving telemetry pipelines
- Collaborate with hardware and firmware teams
- Design Edge AI solutions
- Design hybrid edge cloud architectures
- Develop benchmarking suites
- Evaluate model bias and privacy
- Implement on device model update workflows
- Implement secure execution paths
- Maintain technical documentation
- Optimize model latency and energy efficiency
- Optimize models for accelerator backends
- Stay current with edge AI releases
Perks/Benefits
Skills/Tech-stack
C++ | Core ML | Cross Platform Inference | Cross-platform | DSP | Distillation | Embedded Systems | Energy optimization | Federated Learning | Latency optimization | Machine Learning | Memory Optimization | Mobile SoC | Model Compression | Model profiling | Model versioning | NPU | ONNX Runtime | On Device Privacy | Pruning | Python | Quantization | Security | TensorFlow Lite
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