Cerebras
Cerebras
„Cerebras“ kuria vaflio masto dirbtinio intelekto aparatinę įrangą ir integruotą programinę įrangą didelio našumo modelių mokymui bei išvadoms. Jos „Wafer-Scale Engine“ procesorius yra CS-3 sistemos ir „Cerebras Inference Cloud“ pagrindas. Ši debesijos paslauga palaiko su „OpenAI API“ suderinamas darbo eigas ir diegimą vietinėse, debesijos bei kraštinėse aplinkose. Įmonės platforma skirta tokioms taikymo sritims kaip modelių pateikimas, tikslinimas, išankstinis mokymas, realiojo laiko DI agentai, genomika, vaistų kūrimas, kibernetinis saugumas ir įmonių paieška. „Cerebras“ sujungia specializuotus lustus, sistemas ir programinę įrangą organizacijoms, kuriančioms ir valdančioms sudėtingus dirbtinio intelekto darbo krūvius. Įmonėje dirba 501–1 000 darbuotojų.

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.

Aprašymas

  • 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

Reikalavimai

  • 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

Privalumai

  • 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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