Edge AI Engineer
Tasks
- 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
- Implement on device model updates and rollback
- Implement secure execution and model protection
- Maintain technical documentation and runbooks
- Optimize for accelerator backends
- Optimize model performance for latency and energy
- Support responsible AI evaluations
- Translate edge AI hardware and software updates into recommendations
Perks/Benefits
- N/A
Skills/Tech-stack
Benchmarking | Bias Evaluation | C plus plus | Core ML | DSP | Edge Cloud | Edge inference | Energy Efficiency | Federated Learning | Hardware Architecture | Hybrid Edge Cloud | Knowledge Distillation | Latency optimization | Machine Learning | Memory Optimization | Mobile GPUs | Mobile SoCs | Model Compression | Model Deployment | NPU | ONNX Runtime | On Device Update | Privacy | Pruning | Python | Quantization | Rollback | Security | Telemetry | TensorFlow Lite | Versioning
Education
Roles
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