ML Software Engineer
Tasks
- Bridge inference code to hardware acceleration using C++
- Build server side Swift frameworks for inference distribution
- Coordinate work across multi node inference clusters
- Distribute and coordinate ML inference across acceleration hardware
- Implement new inference functionality
- Improve machine learning inference stability and performance
- Integrate inference code into production service stack
Perks/Benefits
Skills/Tech-stack
Asynchronous programming | Batching | C++ | Concurrency | Distributed Systems | GRPC | Go | Inference Serving | Java | KV cache | Machine Learning | OpenTelemetry | Protocol Buffers | Python | Quantization | RPC | Rust | Server Side | Server Side Swift | Sparsity | Splunk | Swift | Tokenization
Education
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