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Research Scientist - Large Language Model

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Luma AI

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Location:
United States , Palo Alto

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Contract Type:
Not provided

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Salary:

250000.00 - 450000.00 USD / Year

Job Description:

This is a rare opportunity to help define the future of large-scale language models. You will work across the entire lifecycle of model development — from large-scale pre-training, to targeted mid-training, to post-training alignment and capability refinement. You will operate at the frontier of scaling laws, reasoning, and alignment, directly shaping how foundation models learn, generalize, and behave in real-world deployments.

Job Responsibility:

  • Architect and scale large autoregressive language models
  • Design improved pre-training objectives to enhance reasoning, knowledge retention, and compositional generalization
  • Develop mid-training strategies such as continued pre-training, domain adaptation, curriculum learning, and synthetic data integration
  • Advance post-training techniques, including instruction tuning, preference optimization, reinforcement learning, distillation, and inference-time compute scaling
  • Study and improve long-context modeling, planning depth, and multi-step reasoning behavior
  • Curate and construct massive, high-quality text corpora for pre-training
  • Design synthetic data pipelines for reasoning, tool use, mathematics, coding, and structured problem solving
  • Develop filtering, mixture weighting, and curriculum strategies that shape emergent capabilities
  • Formulate new tasks that improve coherence, logical consistency, factual grounding, and robustness
  • Train frontier-scale language models across large GPU clusters
  • Optimize distributed training (data, tensor, pipeline parallelism), mixed precision, and memory efficiency
  • Build infrastructure for large-scale experimentation, ablations, and reproducibility
  • Improve inference efficiency and support scalable deployment
  • Define and build evaluation frameworks for language intelligence, including: Multi-step reasoning and mathematical problem solving, Coding and structured generation, Knowledge grounding and factuality, Planning and agentic behavior, Instruction following and alignment
  • Track capability development across pre-training, mid-training, and post-training
  • Close the loop between evaluation signals and data/model improvements

Requirements:

  • Strong foundation in machine learning and large language models
  • Deep understanding of autoregressive transformers and large-scale training dynamics
  • Experience with pre-training large models and/or post-training techniques such as instruction tuning, RLHF, preference optimization, or distillation
  • Hands-on experience with PyTorch and distributed training at scale
  • Comfortable operating across research and production environments

Nice to have:

  • Experience training frontier-scale language models from scratch
  • Research contributions in scaling laws, reasoning, alignment, or inference-time compute
  • Experience designing large-scale synthetic reasoning data
  • Expertise in long-context modeling or structured reasoning systems
  • Experience optimizing models for real-world deployment constraints

Additional Information:

Job Posted:
March 13, 2026

Employment Type:
Fulltime
Work Type:
Remote work
Job Link Share:

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