Senior Large-Model Quantization Engineer

KINGFISHER RECRUITMENT (SINGAPORE) PTE. LTD.

Singapore

On-site

SGD 120,000 - 180,000

Full time

2 days ago
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Job summary

KINGFISHER RECRUITMENT (SINGAPORE) PTE. LTD. partners with an innovative semiconductor company building its first overseas R&D team in Singapore. The role focuses on quantization and model compression for LLMs, VLMs, and video generation models across NPU, GPU and CPU platforms.

You will work with algorithm, compiler and hardware teams to optimize accuracy, memory efficiency and inference performance while developing supporting toolkits for automated quantization workflows and debugging.

Qualifications

  • Bachelor's degree in a quantitative discipline; required for entry
  • Familiarity with LLM/VLM algorithms and deployment optimisation techniques
  • Strong Python and C++ programming skills
  • Hands-on PyTorch experience is a plus

Responsibilities

  • Develop and optimize model quantization algorithms for LLMs, VLMs, and video generation models.
  • Balance accuracy, memory efficiency and inference performance across NPU, GPU and CPU.
  • Perform calibration and error analysis to identify sources of accuracy degradation.
  • Collaborate with algorithm, compiler and hardware teams on deployment and optimization.
  • Build quantization tooling and automated workflows for evaluation and debugging.
  • Explore emerging quantization research and translate techniques into production solutions.

Skills

Python
C++
Quantization
Model compression
PTQ/QAT concepts

Education

Bachelor's degree in a quantitative discipline

Tools

PyTorch

Job description

KINGFISHER RECRUITMENT (SINGAPORE) PTE. LTD. partners with an innovative semiconductor company building its first overseas R&D team in Singapore. The role focuses on quantization and model compression for LLMs, VLMs, and video generation models across NPU, GPU and CPU platforms.

You will work with algorithm, compiler and hardware teams to optimize accuracy, memory efficiency and inference performance while developing supporting toolkits for automated quantization workflows and debugging.

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