Staff Software Engineer, Inference Cloud

Cerebras; Sunnyvale (CA); On-site; USD 120,000 - 150,000; Full time

Job summary

A leading AI technology company in Sunnyvale, California, is seeking a skilled software engineer to optimize its AI cloud platform for model training and inference. In this role, you'll enhance deployment efficiency and ensure system reliability and scalability. The ideal candidate should have over 5 years of experience in developing production-grade cloud services and a solid grasp of modern generative AI models. The company emphasizes diverse teams and continuous learning, fostering a collaborative work environment.

Qualifications

• 5+ years as an individual contributor developing production-grade cloud services.
• Experience building ML serving and/or training services, preferably for modern generative AI models.
• Strong problem-solving skills and the ability to thrive in ambiguous, rapidly changing conditions.

Responsibilities

• Optimize deployment for minimal latency and efficient load balancing.
• Ensure high reliability, scalability, security, and observability of training and inference infrastructure.
• Develop tools to map out system bottlenecks and design solutions.

Skills

Production-grade cloud services development

ML serving and training services

Reliability in cloud services

Understanding of AI model architectures

Problem-solving skills

Communication skills

Job description

Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs.

Cerebras' current customers include global corporations across multiple industries, national labs, and top-tier healthcare systems. In January, we announced a multi-year, multi-million-dollar partnership with Mayo Clinic, underscoring our commitment to transforming AI applications across various fields. In August, we launched Cerebras Inference, the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services.

About The Role

As a software engineer on our AI cloud platform, you will work on our cloud platform for AI model training and inference. In this role, you will be responsible for optimizing deployment for minimal latency and efficient load balancing, and on ensuring high reliability, scalability, security, and observability of our distributed training and inference infrastructure. You will define and document production requirements, implement scaling strategies, and ensure robust API server management and high availability.

You will develop tools to map out system bottlenecks and sources of instability, and design and build solutions to address them.

We're looking for talented software engineers who thrive in ambiguity, view change as an opportunity, and have a voracious desire to learn and share knowledge clearly and concisely.

Skills And Qualifications

• 5+ years as an individual contributor developing production-grade cloud services.
• Experience building ML serving and/or training services, preferably for modern generative AI models.
• Experience building high-reliability, production-grade cloud services.
• Familiarity with the latest AI model architectures and efficient implementation of serving systems for these models.
• Strong problem-solving skills and the ability to thrive in ambiguous, rapidly changing conditions.
• Excellent communication skills and a passion for continuous learning and knowledge sharing.

Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.

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