Edge AI Engineer
Tasks
- Apply model compression and quantization
- Build cross platform inference runtimes
- Build privacy preserving telemetry pipelines
- Collaborate with hardware firmware product teams
- Design Edge AI solutions
- Design hybrid edge cloud architectures
- Develop benchmarking suites
- Evaluate responsible AI privacy and bias
- Implement on device model updates versioning rollback
- Implement secure execution and model integrity
- Maintain technical documentation
- Optimize model performance for latency energy memory
- Optimize models for accelerator backends
Perks/Benefits
Skills/Tech-stack
Benchmarking | C++ | Core ML | DSP | Edge Cloud | Edge Computing | Embedded Systems | Energy Efficiency | Federated Learning | Hybrid Edge Cloud | Knowledge Distillation | Latency optimization | Machine Learning | Mobile GPU | Mobile SoC | Model Compression | Model Optimization | NPU | ONNX Runtime | On-device Inference | Privacy | Pruning | Python | Quantization | Security | Telemetry | TensorFlow Lite
Education
N/A
Roles
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