2 days ago
Taipei, TaiwanMid Level / Senior
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.
Categories
About 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 makers and cloud providers integrating baseboard management and platform resiliency. The company was founded in 2017, is privately held, and is headquartered in San Jose, California.