Ai/Ml系统工程师
Tasks
- Coordinate OTA safe update security review workflow
- Define machine learning requirements
- Define scene based quantitative metrics
- Ensure edge deployment constraints for inference
- Ensure machine learning training data quality
- Establish AI performance monitoring KPI system
- Implement data feedback closed loop
- Manage AI data requirements
- Manage progressive validation process
- Manage sim to real engineering closed loop
- Perform physical parameter identification
- Quantify sim to real gaps
- Review machine learning architecture
Perks/Benefits
- N/A
Skills/Tech-stack
Data Quality | Data Quality Management | Edge Computing | Functional Safety | Gap Quantification | IEC 61508 | ISO 26262 | Jira | Machine Learning | Model Deployment | Model Inference | Notion | OTA security | Parameter identification | Physical Parameter Identification | Progressive Validation | Quality management | Reinforcement Learning | Requirements Management | Sim2real | Testing management
Education
Roles
AI | AI/ML Systems Engineer | Engineer | ML Systems Engineer | Systems Engineer
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