Machine Learning Engineer — Inference Optimization
Tasks
- Benchmark model performance across hardware and cloud environments
- Build and maintain inference serving infrastructure
- Contribute to quality scalability and maintainability of ML infrastructure
- Implement optimization techniques for quantization KV cache speculative decoding batching and streaming
- Improve reliability monitoring observability and cost efficiency
- Optimize machine learning inference systems for latency throughput scalability and cost
- Productionize new model architectures and deploy experimental results reliably
- Profile and identify bottlenecks across GPU and CPU inference pipelines
Perks/Benefits
Skills/Tech-stack
Attention Mechanisms | Batching | CUDA | Compute Graphs | Distributed Systems | GPU Performance | GPU Performance Optimization | Hardware optimization | KV cache | Low Latency | Low-Latency Services | Memory Optimization | Model simplification | Neural Networks | ONNX Runtime | Performance optimization | PyTorch | Python | Quantization | ROCm | Speculative decoding | Streaming | TensorRT | Triton | VLLM
Education
N/A
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