Staff AI Inference and Acceleration Engineer
Tasks
- Apply operator fusion
- Apply pruning
- Apply quantization
- Collaborate with silicon vendors
- Define compute budget for inference tasks
- Define hardware friendly model constraints
- Design on board inference architecture
- Evaluate acceleration hardware
- Integrate runtime scheduling and power management
- Map models to accelerators
- Optimize data movement
- Optimize inference toolchains end to end
- Optimize kernel scheduling
- Optimize memory layout
- Partition inference workloads across heterogeneous compute
- Profile inference pipelines
Perks/Benefits
- N/A
Skills/Tech-stack
AI Inference | Benchmarking | C++ | CUDA | Computer Architecture | Edge AI | Embedded Systems | Heterogeneous computing | INT4) | INT8 | JAX | MLIR | Memory hierarchy | Mixed Precision | ONNX | Operator fusion | Profiling | Pruning | Python | Quantization | ROCm | TFLite | TVM | TensorRT | Torch
Education
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