Principal ML Investigator

Responsibilities

• Build and lead a new research team capable of industry-leading research and advanced development
• Organize advanced development topics into a cohesive research agenda
• Adapt novel algorithms and model architectures to run efficiently on the Cerebras wafer-scale platform
• Systematically train, tune, and evaluate models to guide production scenarios
• Collaborate with hardware and software teams to co-design next-generation architectures
• Partner with external customers and academic institutions to drive industry insight and credibility
• Focus on key areas including post-training, RL, dataset curation, LLM pretraining, and sparsity

Requirements

• PhD in Computer Science or a related field
• Strong grasp of ML theory in areas such as post-training, LLM pretraining, or model optimization
• Proven experience engineering ML systems for large-scale production deployment
• Experience leading and mentoring a team of researchers or engineers

Preferred Qualifications

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

About the Company

Cerebras Systems builds the world's largest AI chip, providing the compute power of dozens of GPUs on a single wafer-scale architecture. Our technology delivers industry-leading training and inference speeds, empowering users to run large-scale ML applications effortlessly. Cerebras partners with top model labs and global enterprises to transform the landscape of Generative AI.