Principal Embedded Edge AI Engineer
Tasks
- Apply FMEA SFMEA and PHM for reliability and safety
- Build time series intelligence models
- Deploy AI ML on embedded and edge devices
- Design AI ML models for edge deployment
- Develop anomaly detection models
- Develop embedded inference pipelines in C C++
- Develop predictive maintenance models
- Implement TensorFlow or PyTorch inference on edge
- Integrate ML outputs into real time control loops
- Lead system level debugging validation and performance tuning
- Mentor engineers and guide technical direction
- Optimize models for latency memory footprint and power
Perks/Benefits
- 401k matching
- Cross-training opportunities
- Dental insurance
- Medical insurance
- Paid Holidays
- Paid sick time
- Paid travel opportunities
- Paid vacation
- Vision insurance
Skills/Tech-stack
Anomaly Detection | Artificial Intelligence | C# | C++ | Deep learning | Digital Twin | Edge Computing | Embedded Systems | FMEA | Hardware acceleration | IoT | Machine Learning | Model Compression | PHM | Predictive Maintenance | PyTorch | Quantization | Reinforcement Learning | Rust | SFMEA | TensorFlow | Time Series
Education
Bachelor of Arts | Bachelor of Engineering | Bachelor of Science
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