Edge AI Engineer
Tasks
- Apply quantization pruning and distillation
- Build cross platform inference runtimes
- Build privacy preserving telemetry pipelines
- Design Edge AI solutions
- Design hybrid edge cloud architectures
- Develop benchmarking suites for accuracy latency and energy
- Drive responsible AI bias evaluation
- Implement on device model update versioning and rollback
- Implement secure execution paths and model protection
- Maintain technical documentation and runbooks
- Optimize model latency energy and memory
- Optimize models for accelerator backends
Perks/Benefits
Skills/Tech-stack
Benchmarking | C++ | Core ML | DSP | Device security | Edge Computing | Embedded Systems | Federated Learning | Integrity verification | Knowledge Distillation | Machine Learning | Mobile GPU | Mobile SoC | Model Compression | Model Optimization | NPU | ONNX Runtime | On-device security | Performance Profiling | Privacy-preserving | Privacy-preserving analytics | Pruning | Python | Quantization | Telemetry | TensorFlow Lite
Education
Roles
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