Edge AI Engineer
Tasks
- Apply model compression techniques
- Build edge 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 responsible AI privacy and bias
- Implement on device model update versioning and rollback
- Implement secure execution paths and model protection
- Maintain technical documentation and runbooks
- Optimize model performance for latency energy and memory
- Optimize models for hardware accelerator backends
- Quantize and prune machine learning models
- Review edge AI hardware and software updates
Perks/Benefits
Skills/Tech-stack
Bias Evaluation | C++ | Core ML | DSP | Edge Computing | Embedded Systems | Federated Learning | Hybrid Cloud | Knowledge Distillation | Machine Learning | Mobile GPU | Model Compression | Model Pruning | Model Quantization | NPU | ONNX Runtime | On-device Machine Learning | Privacy | Python | Telemetry | TensorFlow Lite
Education
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