Requirements

Expected technologies

Java

C

C++

Python

Go

JavaScript

Optional technologies

TensorFlow

Kubernetes

Our requirements

• Bachelor’s degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience.
• 3 years of experience writing code in one or more general purpose programming languages (e.g., Java, C, C++, Python, Shell, Go or JavaScript, etc.) and in virtualization and orchestration frameworks.
• System administrator level experience with Linux/Unix systems.
• Experience debugging issues across the hardware/software boundary on enterprise-grade server infrastructure.
• Experience troubleshooting and advocating for customer needs, and triaging technical issues across the stack (e.g., hardware faults, low-level software, networking, virtualization, kernel drivers, firmware, performance).

Optional

• Experience working directly with AI/ML computing hardware, including GPUs or other accelerators.
• Experience with ML frameworks (e.g., TensorFlow, Pytorch), and understanding of the AI/ML training and inference lifecycle.
• Experience working with large-scale 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-prem or cloud environment.
• Excellent troubleshooting, attention to detail, and communication skills.

Your responsibilities

• Manage customer’s problems through effective diagnosis, resolution, or implementation of new investigation tools to increase productivity for customer issues on AI/ML infrastructure.
• 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.
• Work closely with multiple Product and Engineering teams to find ways to improve the product, and interact with our Site Reliability Engineering (SRE) teams to drive high-quality production.
• Be available for non-standard work hours or shifts which may include weekends as needed.