Edge AI Engineer
Tasks
- Apply model compression and quantization
- Build cross platform inference runtimes
- Build privacy preserving telemetry pipelines
- Design Edge AI solutions
- Design hybrid edge cloud architectures
- Develop benchmarking suites
- Implement on device model update and rollback
- Implement secure model protection and integrity verification
- Maintain technical documentation
- Optimize inference for latency and energy
- Optimize models for accelerator backends
- Perform responsible AI privacy and bias evaluation
- Translate hardware and software updates into recommendations
Perks/Benefits
Skills/Tech-stack
C++ | Core ML | DSP | Edge inference | Energy optimization | Federated Learning | Hardware-Aware Optimization | Integrity verification | Knowledge Distillation | Latency optimization | Machine Learning | Memory Optimization | Mobile GPU | Model Compression | Model Deployment | Model Integrity | Model Integrity Verification | NPU | ONNX | ONNX Runtime | Performance Profiling | Privacy & Security | Pruning | Python | Quantization | Telemetry | TensorFlow Lite
Education
Roles
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