Senior ML Engineer (AI Hardware)

Location: Taipei, Taiwan

Company

hirify.global develops silicon-rooted security and management chips, including trusted control and compute units for AI data center infrastructure, combining platform security, BMC/firmware, and on-chip AI.

What you will do

• Optimize training and inference performance across GPU and AI-accelerator infrastructure, including MLOps pipelines.
• Design, train, evaluate, and productionize machine learning models across deep learning, LLM, computer vision, and recommendation use cases.
• Build and optimize inference engines and serving runtimes for real hardware constraints involving latency, memory, and power.
• Develop expertise in at least one specialty area: NPU hardening, systems software, inference runtimes, test and verification harnesses, or security-focused ML.
• Collaborate with RTL and 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.
• Experience with GPU clusters, distributed training, inference-serving optimization, and MLOps pipelines.
• Experience designing, training, evaluating, deploying, and monitoring ML models, including feature engineering and data pipelines.
• Experience with AI chip or hardware-aware ML, such as optimizing inference engines or adapting model architectures and quantization to chip constraints.
• Hands-on experience in at least one specialty area: NPU/AI accelerators, low-level systems software, inference engines, test/verification harnesses, or cybersecurity.

Culture & Benefits

• Work on the full AI silicon cycle, from model development to chip-level deployment.
• Collaborative environment focused on practical, real-world security and infrastructure problems.
• Emphasis on continuous learning, persistence, curiosity, mutual support, and innovation.
• Equal opportunity workplace with a diverse and multifaceted environment.