Machine Learning Engineer — Inference Optimization
Tasks
- Benchmark model performance across hardware and cloud environments
- Build and maintain inference serving infrastructure
- Implement quantization and KV cache optimization
- Implement speculative decoding batching and streaming
- Improve quality scalability and maintainability of ML infrastructure
- Improve reliability monitoring observability and cost efficiency
- Optimize machine learning inference systems for latency throughput scalability operational cost
- Productionize model architectures and translate research results
- Profile and identify bottlenecks in GPU and CPU inference pipelines
Perks/Benefits
Skills/Tech-stack
Attention Mechanisms | Batching | CUDA | Compute Graphs | Distributed Systems | KV cache | Language Models | Large Language Models | Machine Learning | Neural Networks | ONNX Runtime | PyTorch | Quantization | ROCm | Speculative decoding | Streaming | TensorRT | Triton | VLLM
Education
N/A
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