Edge AI Engineer
Tasks
- Analyze and optimize application performance
- Collaborate with cross functional stakeholders for safe deployment
- Contribute to MLOps deployment workflows
- Coordinate code reviews and enforce coding standards
- Develop AI model integration APIs and components
- Integrate AI inference pipelines into software architectures
- Optimize AI models for edge deployment
- Perform AI verification validation and risk management for medical devices
- Profile and optimize memory latency throughput and power
Perks/Benefits
- Discounts on company products
- Employer pension contributions
- Health and wellbeing programs
- Paid leave
- Paid parental leave
Skills/Tech-stack
API Integration | Agile | CI/CD | ClearML | Embedded Systems | IEC 62304 | ISO 14971 | Image Processing | MLOps | Machine Learning | Machine Learning Inference | Model Optimization | ONNX | ONNX Runtime | OpenVINO | Performance Profiling | PyTorch | Python | Reproducible Machine Learning | Signal Processing | Software testing | TensorFlow | TensorFlow Lite | TensorRT | Test automation | Test-Driven | Test-Driven Development | Version control
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
Regions
Countries
States
Cities
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