Cerebras
Cerebras
Cerebras өнімділігі жоғары модельдерді оқытуға және инференске арналған пластина ауқымындағы жасанды интеллект аппараттық құралдары мен біріктірілген бағдарламалық жасақтаманы әзірлейді. Оның Wafer-Scale Engine жүйесі CS-3 жүйесі мен OpenAI API үйлесімді жұмыс процестерін қолдайтын Cerebras Inference Cloud платформасының негізі болып табылады; бұл шешімдер жергілікті инфрақұрылымда, бұлтта және шеткі ортада орналастыруға мүмкіндік береді. Компания платформасы модельдерді ұсыну, дәлдеп баптау, алдын ала оқыту, нақты уақыттағы AI агенттері, геномика, дәрі-дәрмек жасау, киберқауіпсіздік және кәсіпорындық іздеу сияқты қолданбаларға арналған. Cerebras күрделі жасанды интеллект жұмыс жүктемелерін жасайтын және іске қосатын ұйымдарға арналған мамандандырылған чиптерді, жүйелерді және бағдарламалық жасақтаманы біріктіреді; компанияда 501–1 000 қызметкер жұмыс істейді.

Applied AI/ML Scientist

Develop and scale custom language models for Cerebras’ wafer-scale AI hardware. Turn customer challenges into training strategies and agentic AI systems.

Сипаттама

  • Develop tailored large language and deep learning models for customer use cases
  • Work with customer stakeholders to identify AI solutions to business problems
  • Assess feasibility, data quality and readiness, and model architecture when scoping engagements
  • Set project milestones, success measures, and evaluation benchmarks
  • Design and run end-to-end training recipes for custom models
  • Create model adaptation strategies, including continued pretraining, supervised fine-tuning, RLHF, and DPO
  • Manage training pipelines from data preparation and tokenization through hyperparameter tuning and loss analysis
  • Assess model convergence, loss behavior, and gradient stability on specialized hardware
  • Scale training workloads with billions of parameters across Cerebras clusters
  • Develop and optimize agentic system features for tool use, long-context reasoning, and multi-step planning
  • Provide AI/ML expertise in technical deep-dives
  • Build and sustain customer relationships as their primary AI/ML expert
  • Bring customer needs to internal research and engineering teams
  • Work with machine learning and product teams on model architectures, training recipes, and internal case studies
  • Turn successful customer engagements into internal playbooks

Талаптар

  • Hold a master’s or PhD in computer science, machine learning, or a related field
  • Demonstrate expert knowledge of dense transformers, mixture-of-experts, multimodal and sequence models, scaling laws, and training dynamics
  • Show a proven record of training or fine-tuning large models with 1B+ parameters
  • Have direct experience addressing large-scale model training challenges
  • Be highly proficient in Python and PyTorch
  • Have experience with distributed training frameworks
  • Have experience with large-scale distributed data processing pipelines and tools
  • Bring strong collaboration and communication skills
  • Work independently and with a team in a dynamic environment
  • Manage multiple projects and adapt as customer needs change
  • Present complex technical findings to audiences from C-suite executives to research scientists

Артықшылықтар

  • Help build an AI platform designed to move beyond GPU constraints
  • Publish and open-source advanced AI research
  • Work with one of the world’s fastest AI supercomputers
  • Combine startup energy with job stability
  • Join a straightforward, non-corporate culture that respects individual beliefs
  • Access ongoing learning, growth, and support

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