Edge AI Engineer
Tasks
- Apply pruning and distillation
- Build cross platform inference runtimes
- Build privacy preserving telemetry pipelines
- Collaborate with hardware, firmware, and product teams
- Design Edge AI solutions
- Design hybrid edge cloud architectures
- Develop benchmarking suites
- Evaluate on device privacy and bias
- Implement model compression and quantization
- Implement on device model update and rollback
- Implement secure execution and model integrity verification
- Maintain technical documentation
- Optimize latency energy and memory on edge hardware
- Tune accelerator backend performance
Perks/Benefits
Skills/Tech-stack
Benchmarking | C++ | Core ML | DSPs | Edge AI | Embedded Systems | Federated Learning | Hybrid Cloud | Inference | Knowledge Distillation | Machine Learning | Mobile GPUs | Mobile SoCs | Model Compression | Model Deployment | NPUs | ONNX Runtime | Privacy | Profiling | Pruning | Python | Quantization | Security | Telemetry | TensorFlow Lite | Versioning
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