Lead and build a research-focused ML team to develop post-training/RL, dataset curation, LLM pretraining, and sparsity techniques; adapt algorithms to Cerebras hardware, run systematic model evaluation, and collaborate with internal teams and external partners to drive production deployments and hardware/software co-design.

Lead a manufacturing test engineering team to develop and implement test strategies, automation, and processes. Collaborate with cross-functional teams to improve test efficiency, troubleshoot complex issues, track KPIs, manage budgets, and ensure product quality and reliability.

Design, develop, and maintain manufacturing test automation from PCBA to system level, build GUIs and web portals, support contract manufacturers, deploy infrastructure, troubleshoot test software and hardware defects, and integrate test data for traceability and yield improvement.

As a 3D Physical Design Engineer, you'll design and analyze 3D integrated products, focusing on ASIC/SoC design, power, clock, and cooling analysis with an emphasis on physical design methodology.

The Director of Cost Accounting leads cost-related financial activities, ensures accurate costing, and partners with various departments to support company growth and IPO readiness.

Oversee general ledger operations, ensure financial reporting compliance, support audits, maintain internal controls, and lead accounting initiatives.

The role involves designing AI models and training methods leveraging wafer-scale hardware and collaborating with various teams and partners in AI and computational science.

The R&D Engineer will design and implement performance workloads on Cerebras' wafer-scale hardware, collaborating across teams to advance AI and scientific computing. Responsibilities include optimizing performance models, contributing to the technology roadmap, and publishing research findings.

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.