Principal ML Investigator

Responsibilities

• Build up a team capable of industry research and advanced development.
• Organize various advanced development topics into cohesive agenda.
• Adapt novel algorithms and model architectures to run on the Cerebras platform.
• Systematically train, tune, and evaluate models to guide/advise production scenarios.
• Collaborate with other teams to co-design next-generation hardware and software architectures.
• Collaborate with external partners (customers, academic) to drive insight and credibility.

Skills & Qualifications

• PhD in Computer Science or related field.
• Strong grasp of ML theory in one or more of the following areas: post-training and reinforcement learning, dataset curation and optimization, LLM pretraining, sparsity, domains (coding agents, reasoning agents, generative language, image, video).
• Proven experience engineering ML systems for scale or production deployment.
• Experience leading a team of researchers or engineers.

Preferred Skills & Qualifications

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