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Senior ML Engineer

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Senior ML Engineer in Others new

  • Taipei, Taiwan

Responsibilities

  • Optimize training and inference performance across GPU and AI-accelerator infrastructure, including MLOps pipelines.
  • Design, train, and evaluate ML models, then take them into production.
  • Build or optimize inference engines and serving runtimes for real hardware constraints such as latency, memory, and power.
  • Develop expertise in at least one area including NPU hardening, systems-level software, inference engines, test or verification harnesses, or security-focused ML.
  • Collaborate with RTL, hardware, firmware, and QA teams to ship AI features from training through deployment and monitoring.

Requirements

  • Bachelor’s degree required; a Master’s degree is preferred.
  • 3–5+ years of hands-on AI/ML experience.
  • Hands-on experience with AI/ML infrastructure and performance, including GPU clusters, distributed training, inference-serving optimization, and MLOps pipelines.
  • Experience designing, training, and evaluating ML models.
  • Experience taking models into production, including feature engineering, data pipelines, and deployment.
  • Experience optimizing inference engines for specific chips or adapting model architecture or quantization to chip constraints.
  • Hands-on experience in at least one specialty area: NPU or AI-accelerator development, systems software, inference engines or runtimes, test or verification harnesses, or cybersecurity applications of AI.

Axiado

Axiado builds hardware-anchored platform security for servers and infrastructure, centered on its Trusted Control/Compute Unit (TCU) processor with root-of-trust functions and AI-based threat detection. It sells security silicon, firmware, and reference platforms to server and network equipment m...

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