Machine Learning Engineer — Inference Optimization
Tasks
- Benchmark model performance across hardware environments
- Build and maintain inference serving infrastructure
- Implement quantization and KV cache optimization
- Implement speculative decoding batching and streaming techniques
- Improve system reliability monitoring and observability
- Optimize cost efficiency under production workloads
- Optimize machine learning inference systems to improve latency throughput scalability and operational cost
- Productionize new model architectures from research results
- Profile and identify bottlenecks across GPU and CPU inference pipelines
Perks/Benefits
- Close collaboration
- Engineering focused culture
- Equity participation
- Flexible remote work
- High ownership
Skills/Tech-stack
Attention Mechanisms | Batching | CUDA | Compute Graphs | GPU Performance | GPU Performance Optimization | Inference Serving | KV cache | Kernel tuning | Machine Learning | Model simplification | Neural Networks | ONNX Runtime | Performance optimization | PyTorch | Quantization | Speculative decoding | Streaming | TensorRT | Triton | VLLM
Education
N/A
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