Edge AI Engineer
Tasks
- Apply model compression and quantization
- Build cross platform inference runtimes
- Build privacy preserving telemetry pipelines
- Design edge AI solutions for constrained devices
- Design hybrid edge cloud architectures
- Develop benchmarking suites for accuracy latency and energy trade offs
- Implement on device model update versioning and rollback
- Implement secure execution paths model protection and integrity verification
- Maintain technical documentation and operational runbooks
- Optimize model latency energy and memory
- Optimize models for accelerator backends
- Support responsible AI privacy and bias evaluation
Perks/Benefits
Skills/Tech-stack
C plus plus | Core ML | Deep learning | Edge Computing | Embedded Systems | Federated Learning | Integrity verification | Knowledge Distillation | Machine Learning | Mobile development | Model Compression | ONNX Runtime | Performance Engineering | Privacy & Security | Profiling | Pruning | Python | Quantization | Telemetry | TensorFlow Lite
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
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