Applied AI/ML Scientist

Highlights

• Build custom SOTA models on world's largest AI chip, 56x larger than GPUs.
• Scale multi-billion parameter training on Cerebras Wafer-Scale Engine clusters.
• Design agentic systems with tool-use, long-context reasoning and planning.

Ideal candidate

Applied ML scientist passionate about building and scaling models for real customer impact, bridging research and production. Comfortable owning training end-to-end and translating results for executives to researchers in fast-paced settings.

Requirements

• Experience in large model training and/or post-training
• Deep understanding of training dynamics, convergence and loss analysis
• Expertise in data curation, preprocessing and tokenization
• Mastery of Python and PyTorch with distributed training frameworks
• Experience with large-scale distributed data processing pipelines
• Strong communication skills from C-level to research scientists