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Applied AI/ML Scientist

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Cerebras Systems

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Location:
United Arab Emirates

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Contract Type:
Not provided

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Salary:

Not provided

Job Description:

As an Applied AI Scientist in the FieldML team, you will be responsible for developing and customizing large language models and more broadly large-scale deep learning models to solve specific customer problems. You won't just advise; you will build. You will bridge the gap between state-of-the-art research and real-world applications by helping customers harness the power of the Cerebras Wafer-Scale Engine (WSE) for their AI initiatives. We are looking for experienced AI Scientists who are passionate about the applied side of machine learning - those who enjoy not just reading papers, but implementing, training, and scaling models to solve complex business and scientific problems. You will work on a diverse range of projects, from training bespoke models from scratch to fine-tuning and optimizing the latest Large Language Models (LLMs) for specific industry verticals, to designing and building components for custom agentic systems.

Job Responsibility:

  • Customer Use Case Discovery & Project Scoping
  • Collaborate with customer stakeholders to identify the best approaches to their business problem with AI
  • Contribute to the technical scoping of engagements, including feasibility analysis, data quality/availability/readiness assessments, and the selection of optimal model architectures
  • Define project milestones, success metrics, and rigorous evaluation benchmarks
  • Custom SOTA Models and AI Systems Development
  • Architect and execute end-to-end training recipes for custom models, tailoring model architecture and training recipes to meet customer-specific performance and accuracy requirements
  • Design and implement sophisticated adaptation strategies, including continuous pre-training on private datasets, supervised fine-tuning (SFT), and post-training alignment via RLHF or DPO
  • Take full ownership of the training pipeline, from high-performance data preprocessing and tokenization to hyperparameter tuning and loss-curve analysis
  • Navigate the nuances of model convergence on specialized hardware
  • Scale training workloads across Cerebras clusters
  • Build and optimize the core components of agentic systems
  • Technical Customer Leadership
  • Serve as an AI/ML subject matter expert during technical deep-dives
  • Build and maintain strong customer relationships
  • Internal Research and Engineering Collaboration
  • Act as the voice of the customer for internal R&D and engineering teams
  • Partner with internal ML teams and product teams on prioritization of novel model architectures
  • Distill customer-facing successful projects into internal playbooks

Requirements:

  • 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) and direct experience with the challenges of large-scale model training
  • Mastery of Python and PyTorch, experience with distributed training frameworks and large-scale distributed data processing pipelines and tools
  • Strong interpersonal and communication skills
  • Effective in collaborative and fast-paced team settings, able to work autonomously and within a team in a dynamic environment, managing multiple projects and pivoting as customer needs evolve
What we offer:
  • Build a breakthrough AI platform beyond the constraints of the GPU
  • Publish and open source their cutting-edge AI research
  • Work on one of the fastest AI supercomputers in the world
  • Enjoy job stability with startup vitality
  • Our simple, non-corporate work culture that respects individual beliefs

Additional Information:

Job Posted:
February 17, 2026

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