LLM Engineer (Optimization)
Tasks
- Analyze GPU memory and kernel performance
- Apply speculative decoding techniques
- Benchmark inference performance across backends
- Design serving architecture for cost latency throughput tradeoffs
- Develop GPU based LLM inference engine
- Develop model quantization pruning and distillation
- Improve memory efficiency for LLM serving
- Optimize LLM for edge and on device execution
- Optimize LLM inference latency
- Optimize LLM inference throughput
- Optimize LLM runtime for GPU and accelerators
- Profile GPU and runtime bottlenecks
- Use compiler and kernel optimization for inference
Perks/Benefits
- N/A
Skills/Tech-stack
Benchmarking | C++ | CUDA | Cache Compression | Inference Optimization | KV Cache Compression | KV cache | Knowledge Distillation | Kubernetes | Language Models | Large Language Models | MLIR | Model Pruning | Model Quantization | ONNX Runtime | Profiling | PyTorch | Python | Speculative decoding | TVM | TensorRT | Triton
Education
N/A
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