Senior Machine Learning Engineer, Runtime and Serving
Tasks
- Architect ML runtime and serving system
- Build profiling and benchmarking tooling
- Collaborate on system level ML workload analysis
- Develop features for ML inference
- Extend ML compilers and runtimes
- Identify end to end ML bottlenecks
- Integrate ML inference runtimes
- Migrate ML workloads to JAX native runtime
- Optimize hardware aware compute
Perks/Benefits
- N/A
Skills/Tech-stack
Benchmarking | Buffer management | C++ | CUDA | Concurrent Systems | Continuous batching | Custom silicon | Data transfer | Deep learning | Distributed Systems | GPUs | JAX | KV caching | Low Latency | Low-Latency Systems | Machine Learning | Machine Learning Runtime | Model Compression | Model Optimization | Model Serving | ONNX Runtime | OpenXLA | PJRT | Prefix caching | Profiling | PyTorch | Python | Shared Memory | TPUs | TVM | Tensor Buffer Management | Tensor operations | TensorRT | Triton | XLA | Zero copy | Zero-copy data transfer
Education
Regions
Countries
States
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