AI Research Engineer (Kernel & Inference Optimization)
Tasks
- Analyze computational efficiency
- Create test datasets and simulation scenarios
- Design model serving architectures
- Develop inference algorithms
- Establish performance metrics
- Identify and resolve bottlenecks
- Implement inference pipelines
- Integrate serving frameworks into edge pipelines
- Monitor production inference KPIs
- Optimize inference strategies
Perks/Benefits
Skills/Tech-stack
Diffusion Models | Distributed Inference Systems | Distributed inference | Expert parallelism | Flash Attention | GPU Kernels | GPU Programming | Inference Optimization | Inference Systems | KV cache | Language Processing | Machine Learning | Metal Shading Language | Mobile GPU | Mobile GPU Programming | Model Serving | Natural Language | Natural Language Processing | Pipeline parallelism | Pruning | Quantization | Shader Programming | Shading language | Speculative decoding | Tensor Parallelism | Vision Transformers
Education
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