Edge AI Engineer
Tasks
- Apply quantization pruning distillation
- 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
- Drive responsible AI privacy bias evaluation
- Implement on device model update versioning rollback
- Implement secure execution paths model protection integrity verification
- Maintain technical documentation
- Optimize models for accelerator backends
- Tune model performance for latency energy memory
Perks/Benefits
Skills/Tech-stack
C++ | Core ML | DSP | Edge Computing | Federated Learning | Hardware-Aware Optimization | Machine Learning | Mobile GPU | Mobile SoC | Model Benchmarking | Model Compression | Model Distillation | Model Pruning | Model Quantization | NPU | ONNX Runtime | Performance Profiling | Privacy Preserving Data | Privacy-preserving | Python | Secure execution | TensorFlow Lite
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
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