AI Infrastructure Operations Engineer

As an AI Infrastructure Operations Engineer at Cerebras Systems, you will be responsible for managing and operating our advanced AI compute infrastructure clusters. This involves monitoring cluster health, ensuring performance, maximizing compute capacity, and resolving technical challenges. You will also deploy and debug container-based services using Docker, provide around-the-clock support, and contribute to process improvement related to monitoring and support.

To be considered for the AI Infrastructure Operations Engineer position at Cerebras Systems, you typically need 6-8 years of experience in managing complex compute infrastructure. Key qualifications include strong Linux proficiency, containerization experience (especially with Docker and Kubernetes), and Python scripting skills. Expertise in troubleshooting distributed systems and a solid understanding of monitoring tools is essential as well.

Cerebras Systems promotes a dynamic and non-corporate work culture that encourages individual beliefs and ideas. As an AI Infrastructure Operations Engineer, you will find a supportive team focused on continuous learning and problem-solving. The collaborative environment at Cerebras allows you to thrive while tackling complex challenges in a rapidly evolving industry, ensuring that your contributions to AI infrastructure development are recognized and valued.

In the role of AI Infrastructure Operations Engineer at Cerebras Systems, you will utilize various tools and technologies such as Docker for container deployment, Kubernetes for orchestration, monitoring systems for infrastructure health, and Python for automation tasks. Familiarity with cloud platforms like AWS, GCP, or Azure, along with networking technologies like TCP/IP, is also beneficial.

At Cerebras Systems, AI Infrastructure Operations Engineers are encouraged to innovate and contribute to all aspects of AI advancements. With constant exposure to cutting-edge technologies and a supportive learning environment, you’ll have the opportunity to develop your skills, tackle unprecedented challenges in AI compute infrastructure, and make significant contributions to projects at the forefront of the industry, reinforcing your role as a key driver of technological progress.

When answering this question, provide clear examples of your previous experience managing compute infrastructures. Highlight any specific projects that involved large-scale AI systems and detail the challenges you faced and how you overcame them, emphasizing your proactive problem-solving approach.

To answer this question effectively, discuss the monitoring tools you utilize and the specific metrics you track to ensure reliable performance. Explain how you identify and respond to potential issues before they impact operations, illustrating your proactive maintenance strategies.

Highlight your experiences deploying applications within Docker containers. Provide examples of how you have used Docker for resource efficiency and ease of deployment, including any relevant orchestration experience with tools like Kubernetes.

Share a compelling story where you encountered a significant technical issue, the steps you took to troubleshoot it, and the outcome. Emphasize your analytical problem-solving skills and your ability to collaborate with different teams to find a resolution.

Your answer should reflect your passion for AI and your belief in its potential to transform industries. Discuss any specific aspects of AI technology that inspire you, such as breakthroughs in machine learning or opportunities to innovate with powerful hardware solutions like those at Cerebras.

Describe your organizational strategies and time management techniques. Explain how you assess the urgency and impact of tasks, ensuring critical systems remain operational while still accomplishing project-driven goals.

Discuss your commitment to continuous learning through online courses, webinars, and industry publications. Mention how you apply this knowledge to drive innovations within your work environment, showcasing your dedication to staying current in the field.

Convey your communication style and the steps you take to ensure all team members are aligned on objectives and challenges. Highlight any tools or practices you use to promote transparency and cooperation among team members.

Provide a systematic approach to optimizing compute resources, such as load balancing, scaling strategies, and efficient allocation of resources based on workload demands. Illustrate your methodology with examples from your past experiences.

Identify key metrics such as CPU and memory usage, network traffic, storage performance, and job completion times. Discuss how you would interpret these metrics to diagnose performance issues and ensure optimal functioning of the clusters.