Applied AI/ML Scientist

About the role

Cerebras is looking for an Applied AI/ML Scientist to develop and customize large language models and other large‑scale deep learning systems for customer use cases. You will bridge cutting‑edge research and real‑world applications on the Cerebras Wafer‑Scale Engine.

Key responsibilities

• Collaborate with customers to discover use cases, scope projects, assess data readiness, and select optimal model architectures.
• Design and execute end‑to‑end training recipes for custom models, including continuous pre‑training, supervised fine‑tuning, and alignment techniques such as RLHF or DPO.
• Own the full training pipeline: data preprocessing, tokenization, hyper‑parameter tuning, loss‑curve analysis, and scaling workloads across Cerebras clusters.
• Build and optimise core components of agentic systems, focusing on tool use, long‑context reasoning, and multi‑step planning.
• Act as the AI/ML subject‑matter expert for customers, translating requirements into precise training recipes and maintaining strong relationships.

Required profile

• Master’s or PhD in Computer Science, Machine Learning, or a related field.
• Expert‑level understanding of modern model architectures (dense transformers, MoEs, multimodal and sequence models) and training dynamics.
• Proven track record of training or fine‑tuning large models (1 B+ parameters) on high‑performance hardware.
• Strong communication skills, able to present technical results to audiences ranging from C‑level executives to research scientists.

Required skills

• Python
• PyTorch
• Distributed training frameworks
• Large language model development and fine‑tuning
• RLHF and DPO alignment techniques
• Data preprocessing and tokenization pipelines
• Hyper‑parameter tuning and loss‑curve analysis