Research Scientist - Large Language Model

Where You Come In 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. What You'll Do This role spans both the "science" and "engineering" dimensions of research - two aspects that are equally important. You will work across modeling, data, systems, and evaluation. Modeling * 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. Data * 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. Systems * 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. Evaluation: 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. Who You Are * 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. What Sets You Apart (Bonus Points) * 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. Your application are reviewed by real people.

Created: 2026-04-15