Edge AI Engineer
Tasks
- Align AI capabilities with device constraints
- Apply model compression and quantization
- Build cross platform inference runtimes
- Build privacy preserving telemetry pipelines
- Design Edge AI solutions
- Design hybrid edge cloud architectures
- Develop benchmarking suites for accuracy and latency
- Ensure responsible AI privacy and bias evaluation
- Implement on device model update and rollback
- Implement secure model execution and integrity verification
- Maintain technical documentation and runbooks
- Optimize model performance for latency energy and memory
Perks/Benefits
Skills/Tech-stack
Benchmarking | Bias Evaluation | C++ | Core ML | DSP | Embedded Systems | Energy Efficiency | Federated Learning | Knowledge Distillation | Latency optimization | Machine Learning | Mobile GPU | Mobile SoC | Model Compression | Model Optimization | NPU | ONNX Runtime | Privacy | Profiling | Pruning | Python | Quantization | Security | Telemetry pipelines | TensorFlow Lite
Education
Roles
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