Embedded AI Engineer
Tasks
- Build edge inference runtimes
- Build privacy preserving telemetry pipelines
- Collaborate with hardware/firmware teams
- Design Edge AI solutions
- Design hybrid edge cloud architectures
- Develop benchmarking suites
- Drive responsible AI bias evaluation
- Implement model quantization pruning distillation
- Implement on device model update versioning rollback
- Implement secure model execution and integrity verification
- Maintain technical documentation
- Optimize model performance for latency energy memory
- Optimize models for accelerator backends
Perks/Benefits
- N/A
Skills/Tech-stack
C++ | Core ML | Edge AI | Federated Learning | Knowledge Distillation | Machine Learning | Model Compression | Model Deployment | Model versioning | ONNX Runtime | On-device Inference | Privacy | Pruning | Python | Quantization | Secure execution | Telemetry | TensorFlow Lite
Education
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