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