AI Systems Engineer

Company Description

VerifAIX, Inc. is transforming semiconductor verification with AI-powered technology purpose-built for today’s complex SoCs, chiplets, and protocol IPs. The company focuses on accelerating and improving verification workflows for cutting-edge semiconductor designs.

Team members work at the intersection of artificial intelligence and hardware engineering to address high-impact industry challenges. VerifAIX offers opportunities to contribute to innovative tools and methodologies that shape the future of chip verification.

Role Description

The AI Systems Engineer will design, implement, and maintain AI-driven systems that support semiconductor verification workflows in a hybrid environment based in Cupertino, CA, with some work-from-home flexibility.

This full-time role includes configuring and administering system infrastructure, integrating AI models and tools into existing verification pipelines, and optimizing performance and reliability across compute and storage environments.

The engineer will troubleshoot complex system issues, provide technical support to internal teams, and collaborate with software, hardware, and verification engineers to refine system architecture. Daily responsibilities also include monitoring system health, documenting configurations and processes, and contributing to the design of scalable solutions that meet evolving project requirements.

Qualifications

• Strong Systems Engineering and Systems Design skills to architect, integrate, and optimize AI-driven verification platforms.
• Proficiency in Troubleshooting and Technical Support to diagnose, resolve, and prevent system and infrastructure issues.
• Hands-on System Administration experience managing Linux-based environments, networking, storage, and security controls.
• Knowledge of AI/ML workflows, including model deployment, MLOps practices, and performance tuning in high-compute environments.
• Experience with cloud or hybrid infrastructure (e.g., Kubernetes, containers, virtualization) supporting engineering workloads.
• Familiarity with semiconductor or EDA tools, SoC design and verification processes, or related hardware engineering domains is beneficial.
• Bachelor’s or master’s degree in Computer Engineering, Electrical Engineering, Computer Science, or a related technical field, or equivalent practical experience.
• Effective communication skills, ability to collaborate in cross-functional teams, and capacity to work independently in a hybrid setting.