Work closely with multiple Product, Quality, and Engineering teams to improve the product, and interact with our Site Reliability Engineering (SRE) teams to understand behaviors.
Debug platform hardware and silicon-related issues to drive root-cause resolution and develop permanent improvements.
Drive understanding of AI/ML workloads and underlying hardware architectures by troubleshooting, reproducing, determining the cause for customer reported issues, and building tools for faster diagnosis.
Act as a consultant and subject matter expert for internal stakeholders in Engineering and Quality organizations to resolve complex deployment and operational obstacles in AI infrastructure environments.
Minimum qualifications
Bachelor's degree in Computer Science, Management Information Systems, or other technical field, or equivalent practical experience.
6 years of experience with technical infrastructure (deployment, maintenance, and troubleshooting), and quality and reliability of technical infrastructure.
6 years of debug or validation experience with CPU, dGPU, or TPU
5 years of experience with hardware debug (silicon debug, platform debug, IO interface, or memory analysis).
Experience debugging technical issues across the stack (hardware faults, low-level software, networking, virtualization, kernel drivers, firmware, or performance)
Experience with Linux/Unix systems and debugging issues across the hardware/software boundary on enterprise-grade server infrastructure.
Preferred qualifications
Experience working with large-scale distributed systems, and familiarity with common solutions, design patterns, or best practices.
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), and understanding of the AI/ML training and inference lifecycle.
Familiarity with containerization and orchestration technologies like Kubernetes or Slurm in an on-prem or cloud environment.
Understanding of memory and high-speed IO technologies.
Bachelor's degree in Computer Science, Management Information Systems, or other technical field, or equivalent practical experience.
6 years of experience with technical infrastructure (deployment, maintenance, and troubleshooting), and quality and reliability of technical infrastructure.
6 years of debug or validation experience with CPU, dGPU, or TPU
5 years of experience with hardware debug (silicon debug, platform debug, IO interface, or memory analysis).
Experience debugging technical issues across the stack (hardware faults, low-level software, networking, virtualization, kernel drivers, firmware, or performance)
Experience with Linux/Unix systems and debugging issues across the hardware/software boundary on enterprise-grade server infrastructure.
