Autonomy Engineer - Deep Learning Model Acceleration
Tasks
- Build SDKs for autonomous machine learning workflows
- Build deep learning inference acceleration solutions
- Deploy models and monitor performance
- Design and implement MLOps workflows
- Develop training efficiency methods
- Drive architecture development testing deployment and monitoring
- Implement GPU kernels for custom architectures
- Improve power efficiency for inference
- Optimize throughput and latency
- Profile computer vision models performance
- Set up model re training pipelines
- Support security and compliance for ML infrastructure
- Use training and runtime frameworks for optimization
Perks/Benefits
- N/A
Skills/Tech-stack
CUDA | Computer Vision | Data Preparation | Deep learning | Edge Deployment | GPU Computing | GPU Kernels | MLOps | Machine Learning | Machine Learning Inference | Model Deployment | Model Monitoring | Model retraining | Optimization | Performance Profiling
Education
N/A
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