AI Research Engineer (Kernel & Inference Optimization)
Tasks
- Build inference test harnesses
- Create evaluation datasets and simulations
- Design model serving architectures
- Enable low latency high throughput scalable inference
- Identify bottlenecks in production
- Implement inference algorithms
- Integrate inference frameworks into production pipelines
- Monitor performance metrics
- Optimize computational efficiency
- Optimize inference pipelines
Perks/Benefits
Skills/Tech-stack
Diffusion Models | Distributed Inference Systems | Distributed inference | Edge Computing | Expert parallelism | Flash Attention | GPU Kernels | Inference Optimization | Inference Systems | KV cache | Language Processing | Latency optimization | Low Latency | Low Memory | Machine Learning | Memory Optimization | Mobile optimization | Model Architecture | Model Serving | NLP | Natural Language | Natural Language Processing | On-device Inference | Pipeline parallelism | Pruning | Quantization | Response Optimization | Speculative decoding | Tensor Parallelism | Throughput Optimization | Token Response Optimization | Vision Transformers
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
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