Platform Software Engineer – Cerebras AI Cloud

As a Platform Software Engineer at Cerebras Systems, your responsibilities will include optimizing deployment processes for minimal latency and ensuring efficient load balancing within our AI cloud platform. You will be tasked with documenting production requirements, implementing scalable solutions, and managing our API server for high availability and reliability. Furthermore, identifying system bottlenecks and creating effective solutions will be a key part of your role.

Cerebras Systems is looking for candidates with at least 5 years of experience in developing production-grade cloud services. Ideal candidates will have experience in ML serving and/or training services, especially with modern generative AI models. A strong understanding of AI model architectures and the ability to problem-solve in rapidly changing conditions are also crucial for this position.

To excel in the Platform Software Engineer position at Cerebras Systems, embrace a culture of continuous learning and knowledge sharing. Be prepared to thrive in dynamic environments where change is a constant, and focus on developing strong problem-solving abilities. Communication skills are equally vital as you will work collaboratively with cross-functional teams to drive innovation in our cutting-edge AI solutions.

As a Platform Software Engineer at Cerebras Systems, you will work on exciting projects involving the optimization of our AI cloud platform for both model training and inference. You will engage in designing and implementing solutions to achieve high reliability, scalability, and security for our cloud services, contributing to groundbreaking advancements in the AI sphere.

The culture at Cerebras Systems is distinctively non-corporate, valuing each individual's beliefs and fostering a collaborative environment. As a Platform Software Engineer, you will be encouraged to contribute your unique insights while experiencing the stability of a solid company backed by vibrant startup energy. Our team thrives on mutual support, continuous growth, and numerous learning opportunities.

When answering this question, highlight specific projects where you optimized cloud services for AI applications. Discuss the measures you implemented to reduce latency and improve efficiency, and be sure to focus on quantifiable results.

Discuss your systematic approach to identifying and resolving bottlenecks, including tools you've used for monitoring and evaluating system performance, as well as teams you've collaborated with to develop solutions.

Use a specific scenario where you successfully scaled a cloud service, detailing the challenges faced and the strategies you employed to manage increased demand while maintaining service reliability.

Talk about your familiarity with various AI model architectures. Mention any specific models you've worked with and how your experience contributes to your understanding of their implications for cloud services.

Answer this by outlining the methodologies and tools you would use to handle deployment, monitoring, and maintenance of services to ensure they meet necessary reliability and scalability benchmarks.

Explain your strategies for API server management, including load balancing techniques, failover strategies, and any specific tools or frameworks you prefer to use to ensure high availability.

Discuss your approach to breaking down ambiguous challenges into manageable parts, gathering data, and collaborating with team members to devise effective solutions.

Give a comprehensive overview of the tools and technologies you are proficient with, relating them to how they’ve influenced your work in developing cloud services, particularly with AI applications.

Express your commitment to continuous learning and how you engage in knowledge sharing. You might reference specific communities you participate in, courses you take, or mentorship experiences.

Articulate your passion for AI, focusing on the unique technology and solutions offered by Cerebras Systems, and how you see yourself contributing to this innovative environment.