Autonomy Engineer - Deep Learning Infrastructure
Tasks
- Build deep learning inference infrastructure
- Deploy models and set up monitoring
- Develop SDKs for autonomous machine learning workflows
- Enable model re training pipelines
- Identify bottlenecks and optimizations
- Implement GPU kernels for optimized inference
- Implement end to end MLOps workflows
- Improve training efficiency
- Optimize deep learning inference performance
- Profile computer vision workloads
- Uphold engineering standards
Perks/Benefits
- N/A
Skills/Tech-stack
CUDA | Computer Vision | Deep learning | Edge Computing | GPU | Image Processing | Inference Optimization | Language Models | MLOps | Machine Learning | Model Deployment | Model Monitoring | Model Training | Object Detection | Optical Flow | PyTorch | Python | SDK development | Security Compliance | Segmentation | TensorFlow | Video Processing | Vision Language Models | Vision-language
Education
N/A
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