Principal ML Investigator

Cerebras
Sunnyvale
Workplace: OnsiteFull timeFunction: Communications, PR & CommunityEducation: phdSkills: ["Leadership","Analytical thinking","Collaboration"]

Build and lead a new ML effort by partnering with ML leaders to define the agenda, grow a capable team, and drive advanced research and development. Work across post-training/reinforcement learning, dataset curation, LLM pretraining, sparsity, and agentic domain capabilities. Adapt novel algorithms and model architectures to run on the Cerebras platform, train/tune/evaluate models, and collaborate with internal teams and external partners.

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FursaFursa
Cerebras
Cerebras
9 months ago

Principal ML Investigator

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Source: Company careers pageValidated by: Fursa AI
Last checked: 16 hours agoStatus: Live

Job Summary

Build and lead a new ML effort by partnering with ML leaders to define the agenda, grow a capable team, and drive advanced research and development. Work across post-training/reinforcement learning, dataset curation, LLM pretraining, sparsity, and agentic domain capabilities. Adapt novel algorithms and model architectures to run on the Cerebras platform, train/tune/evaluate models, and collaborate with internal teams and external partners.
Location: Sunnyvale
Workplace: Onsite
Employment Type: Full time
Job Function: Communications, PR & Community
Seniority: Sr. Manager level

Key Responsibilities

  • •Build up and lead a team capable of industry research and advanced development for a new ML effort.
  • •Organize advanced development topics into a cohesive agenda aligned with existing ML teams and responsibilities.
  • •Adapt novel algorithms and model architectures to run on the Cerebras platform.
  • •Systematically train, tune, and evaluate models to guide and advise production scenarios.
  • •Collaborate across teams to co-design next-generation hardware and software architectures, and with external partners to drive insight and credibility.

Key Requirements

  • •PhD in Computer Science or related field.
  • •Strong grasp of ML theory in one or more areas such as reinforcement learning, dataset curation, LLM pretraining, sparsity, or relevant domains.
  • •Proven experience engineering ML systems for scale or production deployment.
  • •Experience leading a team of researchers or engineers.
  • •Ability to analytically model or optimize system performance.
Education:PhD / Doctorate in Computer Science
Skills:LeadershipAnalytical thinkingCollaboration
Tech Stack:TritonLLMsGPTLlamaCerebras

Company Brief

Cerebras
Designs and builds wafer-scale AI accelerators and systems for large-scale deep learning workloads, delivering specialized hardware and software to accelerate model training and inference for enterprises and research institutions.
Industry: Hardware Devices
Company Size: Large (251 to 1,000 employees)
Growth: Scaleup
Headquarters: Sunnyvale, United States
Founded: 2016
WebsiteLinkedIn