← All roles

Applied AI/ML Scientist

Cerebras· Software Engineering
Apply on company site
UAEFull-timePosted 3mo ago

About the role

Applied AI Scientist in the FieldML team focused on developing and customizing large language models and large-scale deep learning models to solve customer problems, bridging research and real-world applications using Cerebras WSE hardware.

Responsibilities

  • Customer Use Case Discovery & Project Scoping: Collaborate with customer stakeholders to identify the best approaches to their business problem with AI; Contribute to technical scoping including feasibility, data readiness assessments, and model architecture selection; Define project milestones, success metrics, and evaluation benchmarks.
  • Custom SOTA Models and AI Systems Development: Architect and execute end-to-end training recipes for custom models; design adaptation strategies (continuous pre-training, supervised fine-tuning, RLHF/DPO); own the training pipeline (preprocessing, tokenization, hyperparameter tuning, loss-curve analysis); analyze convergence on specialized hardware; scale training across Cerebras clusters for multi-billion parameter models; build/optimize core components of agentic systems.
  • Technical Customer Leadership: Serve as AI/ML subject matter expert during technical deep-dives; build and maintain strong customer relationships as their go-to AI/ML expert.
  • Internal Research and Engineering Collaboration: Act as the voice of the customer for internal R&D; partner with ML and product teams on model architectures and training recipes; distill customer success into internal playbooks.

Qualifications

  • Education: Master’s or PhD in Computer Science, Machine Learning, or related fields.
  • Broad Deep Learning Expertise: Expert-level understanding of modern model architectures (dense transformers, MoEs, multimodal/sequence models), scaling laws, and training dynamics.
  • Hands-on Training Experience: Proven track record of training and/or fine-tuning large models (1B+ parameters) and managing large-scale training challenges.
  • Engineering Proficiency: Mastery of Python and PyTorch; experience with distributed training frameworks and large-scale distributed data processing pipelines.
  • Strong Interpersonal and Communication Skills: Ability to communicate complex results to diverse audiences (C-level to researchers) and work autonomously or in teams in a dynamic environment.

Skills

Required:Large-scale model trainingPythonPyTorchDistributed trainingCommunication
Last updated Aug 30, 2026. Interested? Apply on the company site.

About Cerebras

Cerebras is the go-to platform for fast and effortless AI training. Learn more at cerebras.ai.

Cerebras is the go-to platform for fast and effortless AI training.

AICerebras Wafer-Scale Enginechipshardwareinferenceliquid-ai-recruiting-targetmultimodalsetter-30
Company profileWebsite

More open roles at Cerebras