Autonomy Engineer - Deep Learning Infrastructure
San Mateo, California, United States
USD 170K-236K Mid-level Full Time
Tasks
- Build and scale deep learning inference infrastructure
- Design MLOps workflows for deployment monitoring and retraining
- Develop SDKs for autonomous ML workflows
- Develop high performance deep learning inference
- Implement GPU kernels for custom architectures
- Improve training efficiency methods
- Optimize power efficiency for inference
- Profile models to find bottlenecks
- Uphold engineering standards for ML systems
Perks/Benefits
Skills/Tech-stack
CUDA | Computer Vision | Deep learning | Edge Deployment | GPU Kernels | GPU Programming | Image Segmentation | Inference Optimization | Language Models | MLOps | Machine Learning | Machine Learning Inference | Machine Learning Inference Optimization | Model Deployment | Model Efficiency | Model Monitoring | Model profiling | Object Detection | Object Tracking | Optical Flow | Power Optimization | Retraining | SDK development | Security Compliance | Video Processing | Vision Language Models | Vision-language
Education
N/A
Regions
Countries
States
Cities
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