AI Research Engineer (Kernel & Inference Optimization)
Tasks
- Analyze computational efficiency and diagnose bottlenecks
- Apply empirical research to improve inference performance
- Build and monitor inference tests in simulated and production environments
- Create test datasets and simulation scenarios
- Design model serving architectures
- Establish performance metrics and benchmarks
- Integrate inference frameworks into edge and on device pipelines
- Optimize inference latency throughput and memory usage
Perks/Benefits
- Career growth
- Collaborative research environment
- English communication support
- Remote work opportunity
Skills/Tech-stack
Diffusion Models | Distributed Inference Systems | Distributed inference | Edge Computing | Expert parallelism | Flash Attention | GPU Kernel Development | High Throughput | Inference Optimization | Inference Systems | KV cache | Kernel development | Learning models | Low Latency | Machine Learning | Machine Learning Models | Memory Optimization | Model Serving | Model architectures | NLP | Parallel Computing | Performance Benchmarking | Pipeline parallelism | Pruning | Quantization | Speculative decoding | Tensor Parallelism | Vision Transformers
Education
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