Applied AI/ML Scientist

The role

You will develop and customize large language models and large-scale deep learning models to solve customer problems. You will bridge the gap between research and real-world applications by helping customers use the Cerebras Wafer-Scale Engine.

What you will do

• Collaborate with customer stakeholders to identify AI approaches to business problems.
• Contribute to technical scoping, feasibility analysis, and data assessments.
• Define project milestones, success metrics, and evaluation benchmarks.
• Architect and execute end-to-end training recipes for custom models.
• Design and implement adaptation strategies like continuous pre-training, SFT, RLHF, or DPO.
• Take ownership of the training pipeline including preprocessing, tokenization, and hyperparameter tuning.
• Analyze model convergence and loss dynamics on specialized hardware.
• Scale training workloads across Cerebras clusters.
• Build and optimize core components of agentic systems.
• Serve as an AI/ML subject matter expert and build customer relationships.

Required qualifications

• Master’s or PhD in Computer Science, Machine Learning, or related fields.
• Expert-level understanding of modern model architectures including dense transformers, MoEs, multimodal and sequence models, scaling laws and training dynamics.
• Proven track record of training and/or fine-tuning large models (1B+ parameters).
• Direct experience with the challenges of large-scale model training.
• Mastery of Python and PyTorch.
• Experience with distributed training frameworks.
• Experience with large-scale distributed data processing pipelines and tools.
• Effective in collaborative and fast-paced team settings.
• Able to work autonomously and within a team in a dynamic environment.
• Able to present complex technical results to diverse audiences.

About the company

Cerebras Systems builds the world's largest AI chip. The company works with leading model labs, global enterprises, and cutting-edge AI-native startups.