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Machine Learning Engineer - Model Optimization

๐Ÿ•’ 9 days ago
๐Ÿ“ ๐Ÿ‡ซ๐Ÿ‡ท France - Remote๐Ÿ’ฐ โ‚ฌ75k - โ‚ฌ90k / year๐ŸŽน Mid-level๐Ÿ—ฃ๏ธ Machine Learning Engineer๐Ÿ“ข ๐Ÿ‡ฌ๐Ÿ‡ง English Required๐Ÿ“ข ๐Ÿ‡ซ๐Ÿ‡ท French Required๐Ÿ’ผ Full-Time
Machine LearningDeep Neural NetworksPytorchPython

๐Ÿ“œ Description

  • Profile and analyze machine learning models to identify computational, memory, and data-movement bottlenecks.
  • Explore trade-offs between model output quality and computational cost, including latency, throughput, and memory footprint.
  • Develop methodologies for hardware-aware model optimization and neural network architecture search.
  • Apply model optimization techniques such as quantization, mixed-precision inference, and model compression.
  • Develop and maintain model export, benchmarking, and deployment pipelines across frameworks like PyTorch and ONNX.
  • Evaluate deployment strategies for mapping models onto heterogeneous processing units.

๐Ÿ› ๏ธ Requirements

  • Strong understanding of machine learning and deep neural network architectures.
  • Hands-on experience developing machine learning models using frameworks such as PyTorch.
  • Proficiency programming in Python.
  • Experience analyzing the computational characteristics of neural networks.
  • Familiarity with techniques such as model architecture search and quantization.
  • Experience with machine learning inference and deployment technologies like ONNX and TensorRT.
  • Ability to reason across different layers of the ML deployment stack.
  • Familiarity with professional software development practices and tools.

โœจ Benefits

  • Transportation/Commute: Commuter
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