Join the SOTA Training Platform team to bring up ML models on Cerebras systems, enhancing performance across the software stack and debugging issues.

The role involves solving complex signal integrity and power integrity challenges in advanced AI compute systems, focusing on high-speed interfaces, power delivery networks, and advanced packaging. The engineer will perform analyses, lead troubleshooting efforts, and collaborate with design teams to ensure optimal performance.

The Cybersecurity GRC Manager will enhance governance, risk, and compliance programs, utilizing technical security knowledge and AI tools to optimize workflows and compliance in cloud environments.

Join Cerebras Systems to optimize and develop frontend compiler infrastructure for PyTorch models on their unique wafer-scale AI platform, focusing on model representation and optimization.

As a Performance Reliability Engineer, you will optimize performance and reliability of ML systems, analyze workloads, enhance collaboration with cross-functional teams, and influence architecture design.

Manage and curate the AI models portfolio, collaborate on model launches, evaluate model quality, and drive product marketing initiatives.

Lead a team of engineers to develop high-performance software solutions for AI and HPC workloads while mentoring team members and overseeing technical direction.

Join the Inference Core Model Bringup team to bring up ML models on Cerebras CSX systems, focusing on performance, optimization, and debugging.

As a Performance Engineer, you will optimize CPU and memory subsystems for high-performance ML workloads on x86 machines, develop algorithms for data movement, and engage with the AI community to enhance our AI platform.

Lead the Inference ML team in developing tools and APIs for large-scale ML applications, enhancing performance and usability, while collaborating across engineering teams.

The role involves developing an embedded test framework, creating test automation, improving test coverage, and collaborating across teams to raise software quality.

The Applied AI Scientist will develop large language models and deep learning solutions, customizing AI systems to meet client needs, and collaborate with stakeholders for project scoping and model architecture selection.

Design and operate the Cerebras Inference Platform by developing backend services and APIs, improving observability, and mentoring engineers.

Assist in deploying and monitoring Cerebras AI infrastructure, perform troubleshooting, collect telemetry, and learn through shadowing senior engineers.

The Applied Machine Learning Research Scientist will translate ML techniques into scalable systems, improve LLM performance, and optimize workflows while collaborating closely with researchers and engineers.

The role involves creating program schedules, managing project documents, overseeing hardware deployment, and working with engineering teams on AI systems.

Join the Kernel Reliability team to improve the reliability of compute clusters, assist in debugging, and enhance system tools alongside hardware teams.

The Software Automation Engineer will design and deliver software solutions to improve operational efficiency, develop automation frameworks, and collaborate with teams to enhance reliability and streamline processes.

Oversee design verification for AI/ML accelerators, managing engineering staff and ensuring successful project delivery through methodologies and simulations.

The Senior WAN Network Engineer will design, implement, and manage global WAN services, ensuring high performance and reliability, while collaborating with telecom providers and optimizing network protocols.