Lead ML/Perception Engineer
Tasks
- Architect perception and autonomy software requirements
- Classify operating scenes and trigger behavior
- Design scene detection and runtime activation
- Develop and test perception features with production code
- Develop multimodal data alignment pipelines
- Enable graceful degradation and fallback strategies
- Harden perception against sensor degradation
- Implement sensor fault detection and health monitoring
- Integrate and deploy perception and ML models for low latency
- Integrate multimodal models into perception stack
- Lead extensive testing to meet release schedules
- Lead feature development and code reviews
- Lead perception stack architecture updates
- Track perception performance metrics in field
Perks/Benefits
- Dental
- Disability plans
- Employer match
- Flexible spending account
- Flexible vacation
- Flexible work travel optional
- Health savings account
- Healthcare suite
- Life insurance
- Paid parental leave
- Retirement benefits
- Total wellness program
- Vision
Skills/Tech-stack
C++ | Computer Vision | Contrastive Learning | Data Mining | Data alignment | Data pipeline | Deep learning | Fault detection | Foundation Models | Graceful Degradation | Health Monitoring | Image Segmentation | Language Models | Large Language Models | Linux | Low Latency | Low-Latency Systems | Machine Learning | Model Deployment | Model Optimization | Multi Modal Data Alignment | Multi-Modal | Multi-Modal Learning | Multi-Target Tracking | Multi-modal data | Multimodal Models | Object Detection | Open Vocabulary Recognition | Prompt engineering | PyTorch | Python | Quantization | Real Time | Real-time Systems | Reinforcement Learning | Scene Understanding | Scene classification | Semantic Scene Understanding | Semantic Segmentation | Sensor fault detection | Sensor fusion | Target Tracking | TensorFlow | Time Systems | Vision Language Models | Vision-language
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