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Cerebras
Cerebras
501 – 1,000 कर्मचारी
SaaSकृत्रिम बुद्धिमत्ताहार्डवेयर
Cerebras उच्च-प्रदर्शन वाले मॉडल प्रशिक्षण और इन्फरेंस के लिए वेफर-स्केल AI हार्डवेयर और एकीकृत सॉफ़्टवेयर विकसित करता है। इसका Wafer-Scale Engine CS-3 सिस्टम और Cerebras Inference Cloud को शक्ति देता है, जो OpenAI API-संगत वर्कफ़्लो तथा ऑन-प्रिमाइसेस, क्लाउड और एज वातावरणों में परिनियोजन का समर्थन करता है। कंपनी का प्लेटफ़ॉर्म मॉडल सर्विंग, फ़ाइन-ट्यूनिंग, प्री-ट्रेनिंग, रीयल-टाइम AI एजेंट, जीनोमिक्स, दवा खोज, साइबर सुरक्षा और एंटरप्राइज़ सर्च जैसे अनुप्रयोगों के लिए बनाया गया है। Cerebras चुनौतीपूर्ण कृत्रिम बुद्धिमत्ता वर्कलोड बनाने और संचालित करने वाले संगठनों के लिए विशेषज्ञ चिप, सिस्टम और सॉफ़्टवेयर को एक साथ लाता है तथा इसमें 501–1,000 कर्मचारी हैं।
LinkedIn
कंपनी की नौकरियाँ

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.

USसंयुक्त राज्यCAकैलिफ़ोर्नियाहाइब्रिडपूर्णकालिकमध्य स्तरवरिष्ठआवश्यक भाषा: अंग्रेज़ीकृत्रिम बुद्धिमत्ता
PythonPyTorch

विवरण

  • 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

आवश्यकताएँ

  • 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

लाभ

  • 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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