Develop an in-depth understanding of AI/ML workloads and underlying hardware architectures by troubleshooting, reproducing, determining the root cause for customer-reported issues, and building tools for faster diagnosis.
Act as a consultant and subject matter expert for internal stakeholders in Engineering, Sales, and customer organizations to resolve complex deployment and operational obstacles in AI infrastructure environments.
Minimum qualifications
Bachelor's degree in Computer Engineering, Electrical Engineering, Computer Science, or IT-related field, or equivalent practical experience.
8 years of experience with Linux/Unix systems and experience in debugging issues across the hardware/software boundary on enterprise-grade server infrastructure.
5 years of experience in technical leadership.
3 years of experience with technical infrastructure (e.g., deployment, maintenance, and troubleshooting), and with quality and reliability of technical infrastructure.
3 years of debug or validation experience with CPU, GPU, or TPU.
Experience troubleshooting and triaging technical issues across the stack (e.g., hardware faults, low-level software, networking, virtualization, kernel drivers, firmware, or performance).
Preferred qualifications
Experience working directly with AI/ML computing hardware, including GPUs or other accelerators.
Experience with systems automation, and with systems design and debug.
Experience with ML frameworks (e.g., TensorFlow, PyTorch), with the understanding of the AI/ML training and inference life-cycle.
Experience working with distributed systems, and familiarity with common solutions, design patterns, or best practices.
Familiarity with containerization and orchestration technologies like Kubernetes or Slurm in an on-premises or cloud environment.
Understanding of memory and high-speed IO technologies.
Bachelor's degree in Computer Engineering, Electrical Engineering, Computer Science, or IT-related field, or equivalent practical experience.
8 years of experience with Linux/Unix systems and experience in debugging issues across the hardware/software boundary on enterprise-grade server infrastructure.
5 years of experience in technical leadership.
3 years of experience with technical infrastructure (e.g., deployment, maintenance, and troubleshooting), and with quality and reliability of technical infrastructure.
3 years of debug or validation experience with CPU, GPU, or TPU.
Experience troubleshooting and triaging technical issues across the stack (e.g., hardware faults, low-level software, networking, virtualization, kernel drivers, firmware, or performance).
