Inference Optimization Architect, Speech AI
Tasks
- Apply knowledge distillation
- Apply model pruning
- Apply model quantization
- Build automated model optimization pipelines
- Collaborate with model researchers to deploy to production
- Design speech model serving infrastructure
- Develop CUDA custom kernels
- Implement encoder caching
- Improve batching strategies
- Leverage CUDA and TensorRT acceleration
- Monitor inference costs and resource utilization
- Optimize inference across GPUs and platforms
- Optimize multi threaded inference pipelines
- Optimize streaming latency and throughput
- Profile and benchmark inference bottlenecks
- Use Nsight Compute for GPU debugging
- Use Nsight Systems for GPU profiling
Perks/Benefits
- N/A
Skills/Tech-stack
Batching | CNN | CUDA | Computer Architecture | Dynamic Shapes | GPU Profiling | Inference Server | JAX | Kernel development | Knowledge Distillation | Latency Tuning | Memory Management | Model Compression | Nsight Compute | Nsight Systems | Operating Systems | Process scheduling | Pruning | PyTorch | Python | Quantization | RNN | TRT-LLM | TensorRT | Thread synchronization | Torchserve | Transformers | Triton Inference | Triton Inference Server | VLLM
Education
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