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QuadricQuadricBurlingame, CA

AI Inference Engineer

AI Inference Engineer ports, optimizes, and benchmarks AI/LLM models on Quadric's GPNPU platform for edge devices. Requires 5+ years in model inference frameworks, quantization expertise, and proficiency in C++/Python.

Salary not listed
Hybrid5+ YOEML Engineering

About the role

Responsibilities

  • Quantize, prune and convert models for deployment
  • Port models to Quadric platform using Quadric toolchain
  • Optimize inference deployment for latency, speed
  • Benchmark and profile model performance and accuracy
  • Collaborate across related areas of the AI inference stack to support team and business priorities
  • Develop tools to scale and speed up the deployment
  • Make improvements to SDK and runtime
  • Provide technical support and documents to customers and developer community

Requirements

  • Bachelor’s or Master’s in Computer Science and/or Electrical Engineering
  • 5+ years of experience in AI/LLM model inference and deployment frameworks/tools
  • Experience with model quantization (PTQ, QAT) and tools
  • Experience with model accuracy measures
  • Experience with model inference performance profiling
  • Experience with at least one of the following frameworks: onnxruntime, Pytorch, vLLM, huggingface-transformer, neural-compressor, llamacpp
  • Proficiency in C/C++ and Python
  • Demonstrate good capability in problem solving, debug and communication

Skills

Model QuantizationPtqQatOnnx RuntimePyTorchvLLMHugging Face TransformersNeural CompressorLlama.CppC++PythonModel ProfilingBenchmarkingAi InferenceLlm Deployment

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