AI Research Engineer (Kernel & Inference Optimization)
Tasks
- Build inference pipelines
- Design model serving architectures
- Develop inference algorithms
- Diagnose serving bottlenecks
- Establish performance metrics
- Integrate serving frameworks into production pipelines
- Monitor KPIs
- Optimize computational efficiency
- Optimize inference strategies
- Prepare test datasets and simulation scenarios
- Run inference tests
Perks/Benefits
Skills/Tech-stack
Compute Shaders | Diffusion Models | Distributed Inference Systems | Distributed inference | Edge Computing | Expert parallelism | Flash Attention | GPU Kernels | High Throughput | Inference Optimization | Inference Systems | KV cache | Low Latency | Machine Learning | Memory Optimization | Metal Shading Language | Model Serving | NLP | On-device Inference | Pipeline parallelism | Pruning | Quantization | Resource-Constrained Devices | Shading language | Speculative decoding | Tensor Parallelism | Vision Transformers
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
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