7 hours ago
Taipei, TaiwanMid Level / Senior
Responsibilities
- Optimize training and inference performance across GPU and AI-accelerator infrastructure, including MLOps pipelines.
- Design, train, and evaluate machine-learning models and take them into production.
- Build or optimize inference engines and serving runtimes against latency, memory, power, and hardware constraints.
- Develop expertise in at least one area such as NPU hardening, systems-level software, inference engines, test and verification harnesses, or security-focused ML.
- Collaborate with RTL, hardware, firmware, and QA teams to deliver AI features from training through deployment and monitoring.
Requirements
- 3–5+ years of hands-on AI/ML experience.
- Bachelor's degree required; master's degree preferred.
- Hands-on experience with AI/ML infrastructure, GPU clusters, distributed training, inference-serving optimization, and MLOps pipelines.
- Experience designing, training, and evaluating ML models, including deep learning, LLM, computer vision, or recommendation systems.
- Experience taking models into production, including feature engineering, data pipelines, and deployment.
- AI-chip or hardware-aware ML experience, such as optimizing an inference engine for a specific chip or adapting model architecture or quantization to chip constraints.
- Hands-on experience in at least one specialty area: NPU/AI accelerator, systems software, inference engine/runtime, test/verification harnesses, or cybersecurity.
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.