Senior research Scientist - Machine Learning Systems & Efficiency Engineer
Tasks
- Advise research and product teams on efficiency tradeoffs
- Build benchmarking frameworks and dashboards
- Define best practices and mentor engineers
- Design and optimize high throughput low latency inference systems
- Design scalable distributed serving systems
- Develop and maintain high performance GPU kernels
- Establish efficiency metrics and cost per million inferences
- Implement resource scheduling and elastic workload management
- Implement serving strategies including batching and caching
- Improve GPU utilization with kernel fusion and async pipelines
- Optimize end to end inference system performance
- Optimize model architectures for deployment efficiency
- Profile performance to identify compute memory and communication bottlenecks
Perks/Benefits
- N/A
Skills/Tech-stack
AllGather | AllReduce | Artificial Intelligence | Asynchronous pipelines | Benchmarking | C++ | CUDA | Computer Vision | Diffusion Transformers | Distributed inference | Docker | GPU Kernel | GPU Kernel Development | GPU Performance | GPU performance tuning | GPU pooling | Inference Serving | Kernel Fusion | Kernel development | Kubernetes | Linux | Machine Learning | Mixture of Experts | Model Distillation | Model Pruning | Model Quantization | Multimodal Models | NCCL | NVIDIA Nsight | ONNX Runtime | Performance Tuning | PyTorch Profiler | Python | Resource scheduling | Scheduling optimization | TensorRT | Transformers | Triton
Education
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