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.

The role involves owning and scaling critical components of the Cerebras Developer Console, managing both frontend and backend systems, making architectural decisions, and leading technical execution in a fast-paced environment.

Design and implement low-level components in a compiler toolchain, focusing on LLVM for optimizing code generation for a large AI chip architecture.

Assist in designing and implementing low-level compiler components for Cerebras' architecture, focusing on LLVM toolchain and performance optimization.

The Deployment Engineer will build and operate AI inference clusters, ensure scalable deployments, optimize allocation, and maintain infrastructure. Responsibilities include software updates, telemetry development, and collaborative improvements with teams.

The Manager of AI Infrastructure Operations leads the reliability and performance of AI compute infrastructure, manages escalations, and drives reliability initiatives.

Collaborate on software solutions for AI systems, focusing on performance and usability within an integrated architecture. Gain hands-on experience with advanced hardware and ML frameworks.

Manage corporate and securities matters, oversee SEC reporting, advise on governance and compliance, and support strategic transactions for growth.

The Senior Technical Program Manager is responsible for site and data center operations, leading cross-functional programs, ensuring operational readiness, and managing metrics and KPIs for AI infrastructure.

The Manufacturing Bring-up Engineer oversees system testing and validation, collaborating with cross-functional teams to automate workflows and enhance manufacturing efficiencies.

The Director of Compliance will structure and administer international trade and contract compliance programs, ensuring adherence to regulations and providing counsel to leadership.

Support system-level bring-up processes in manufacturing, collaborate on automation and validate system performance, resolve technical issues and track metrics for continuous improvement.

Responsible for software integration and quality for Cerebras AI platform, focusing on automation, debugging, and cross-team collaboration. Develops QA strategies and testing methodologies to ensure product quality.

Develop and automate configuration for distributed clusters, create monitoring tools, manage cloud operations, and ensure system reliability for Cerebras AI supercomputers.

Design and develop high-performance distributed software for scalable AI training systems, focusing on data pipelines and system efficiency.