Edge AI Engineer
Tasks
- Apply quantization pruning distillation and compression
- Build cross platform inference runtimes
- Build privacy respecting telemetry pipelines
- Collaborate with hardware, firmware, and product teams
- Design edge AI solutions for constrained hardware
- Design hybrid edge cloud architectures
- Develop benchmarking suites for accuracy latency and energy
- Implement on device model update versioning and rollback
- Implement secure execution paths model protection integrity verification
- Maintain technical documentation runbooks and operational procedures
- Optimize latency energy efficiency and memory usage
- Optimize models for accelerator backends
- Stay current with edge AI hardware and software updates
- Support responsible AI privacy and bias evaluation
Perks/Benefits
- N/A
Skills/Tech-stack
Benchmarking | Bias Evaluation | C++ | Core ML | Edge Computing | Embedded Systems | Energy Efficiency | Hardware-Aware Optimization | Inference | Knowledge Distillation | Latency optimization | Machine Learning | Memory Optimization | Mobile GPU | Model Compression | Model Optimization | Model versioning | ONNX | ONNX Runtime | Performance Profiling | Privacy | Pruning | Python | Quantization | Rollback | Secure execution | Telemetry pipelines | TensorFlow | TensorFlow Lite
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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