Research Scientist / Engineer – Foundation Model: Core Research

Luma
Redwood City
Workplace: HybridFull timeFunction: Data Science & Machine LearningEducation: bachelorsSkills: ["First-principles reasoning","Experiment design","Rigorous analysis","Communication","Technical decision-making"]

Architect the reasoning core behind Luma’s world-modeling and foundation-model products. Lead core research across multimodal representations, long-context training, proxy tasks, automated metrics, and scaling laws—while closing the gap between training loss and user experience. Build research infrastructure for production-research parity, reproducibility, and rapid experimentation, delivering measurable improvements through validated modeling and evaluation advances.

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Luma
Luma
1 week ago

Research Scientist / Engineer – Foundation Model: Core Research

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Last checked: 4 hours agoStatus: Live

Job Summary

Architect the reasoning core behind Luma’s world-modeling and foundation-model products. Lead core research across multimodal representations, long-context training, proxy tasks, automated metrics, and scaling laws—while closing the gap between training loss and user experience. Build research infrastructure for production-research parity, reproducibility, and rapid experimentation, delivering measurable improvements through validated modeling and evaluation advances.
Location: Redwood City
Workplace: Hybrid
Employment Type: Full time
Job Function: Data Science & Machine Learning

Key Responsibilities

  • •Drive core research powering Luma’s products by co-designing multimodal representations and advancing long-context training and scaling laws.
  • •Develop proxy tasks and automated metrics to connect training loss to user experience and guide research decisions.
  • •Build research infrastructure for high-velocity work, including production-research parity, reproducibility, and rapid experimentation systems.
  • •Immerse in current models and evaluations to diagnose scaling and quality gaps during the first month.
  • •Ship and validate a modeling or evaluation improvement, then systemize it into scaling laws and infrastructure across the team by months 60–90.

Key Requirements

  • •Bachelor’s, Master’s, or PhD in Computer Science, Machine Learning, Physics, or Mathematics.
  • •First-principles intuition for scaling, including why architectures succeed or fail at scale.
  • •Fluency across frontier AI research and engineering as a single discipline.
  • •Ability to design and rigorously analyze experiments and articulate complex concepts.
  • •Practical experience with distributed or high-performance computing and optimizing training runs on large GPU clusters.
Experience:Frontier AIDistributed computingHigh-performance computing
Education:Bachelor's in Computer Science, Machine Learning, Physics, Mathematics
Skills:First-principles reasoningExperiment designRigorous analysisCommunicationTechnical decision-making
Tech Stack:Multimodal representationsLong-context trainingProxy tasksAutomated metricsScaling lawsDistributed computingHigh-performance computingGPU clustersLow-precision trainingProduction-research parityReproducibility

Company Brief

Luma
Develops AI-powered tools for capturing, editing, and rendering high-quality 3D scenes from photos and videos, enabling creators to generate photorealistic 3D assets and spatial experiences.
Industry: AR/VR & Spatial Computing
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