AI Research Engineer (Kernel & Inference Optimization)
Tasks
- Deploy inference pipelines
- Design model serving architectures
- Develop inference algorithms
- Diagnose serving bottlenecks
- Integrate inference frameworks into production pipelines
- Monitor inference performance metrics
- Optimize GPU kernel performance
- Optimize batch processing
- Optimize inference strategies
- Prepare test datasets and simulation scenarios
- Run inference benchmarks
- Support edge and on device deployment
Perks/Benefits
Skills/Tech-stack
Computer Vision | Deep learning | Diffusion Models | Distributed inference | Edge Computing | Embedded Systems | Expert parallelism | Flash Attention | GPU Kernels | GPU Programming | High Throughput | High-Throughput Systems | Inference Optimization | KV cache | Kernel optimization | Low Latency | Low-Latency Systems | Machine Learning | Memory Optimization | Metal Shading Language | Mobile optimization | Model Serving | NLP | On-device Inference | Pipeline parallelism | Pruning | Quantization | Shading language | Speculative decoding | Tensor Parallelism | Tokenization | Vision Transformers
Education
Bachelor of Science | Doctor of Philosophy | Master of Science | PhD
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