Principal ML Investigator

About the role

Cerebras Systems is building an ML team focused on a new ML effort that aligns with existing teams. It is seeking a Principal Investigator to partner with ML leaders in formulating the effort and building the team and its capabilities. The new team would coordinate with Field ML (customer-facing), Applied ML (new capabilities and applications) and Core ML (adapting algorithms to Cerebras hardware), and could take the same or complementary responsibilities.

Key responsibilities

• Work on post-training and reinforcement learning, dataset curation and optimization, LLM pretraining, sparsity, and domains such as coding and reasoning agents, generative language, image and video.
• Build a team capable of industry research and advanced development.
• Organize advanced development topics into a cohesive agenda.
• Adapt novel algorithms and model architectures to run on the Cerebras platform.
• Train, tune and evaluate models systematically to guide production scenarios.
• Co-design next-generation hardware and software architectures with other teams.
• Collaborate with external partners, including customers and academics, to drive insight and credibility.

Required profile

• PhD in Computer Science or a related field.
• Strong grasp of ML theory in one or more of the listed areas.
• Proven experience engineering ML systems for scale or production deployment.
• Experience leading a team of researchers or engineers.

Preferred skills

• Patents or publications in top-tier conferences or journals.
• Experience with large language models (e.g., GPT family, Llama).
• Distributed training concepts and frameworks.
• Training speed optimizations, such as model architecture transformations or low-level kernel development (e.g., Triton).
• Ability to analytically model or optimize system performance.