Research Scientist - Data

⚡ Research Scientist - Data focus💊 Foundation Models, AI Research Institute🌎 San Francisco Bay Area, USA💸 $200,000 - $350,000 salary + bonusCome join a revolutionary AI research lab in SF Bay Area that is poised to develop & publish high-impact breakthroughs in GenAI - across LLMs and Multimodal AI.As part of the team, you’ll work at the intersection of data, large-scale training, and foundation model innovation. You will collaborate with world-class researchers, data scientists, and engineers to solve critical challenges in creating robust, scalable, and reasoning-capable LLMs. Your research will shape the way data is curated, processed, and leveraged to train the next generation of intelligent systems.Responsibilities:Lead research on data-centric approaches for LLMs, including pretraining corpus design, data valuation, and speculative decoding strategies.Develop pipelines to process challenging data sources into structured and reproducible training datasets.Build and optimize agentic data pipelines, integrating retrieval, self-curation, and multi-agent feedback for high-quality training and evaluation data.Collaborate with researchers on alignment and reasoning-focused training that leverage data-driven approaches for improving LLM capabilities.Prototype and deploy evaluation frameworks to measure data quality, coverage, and downstream impact on LLM reasoning.Publish findings at top-tier venues (e.g., NeurIPS, ICLR, ACL, EMNLP) and represent the institute at international conferences.Contribute to open-source tools, datasets, and benchmarks that advance the global foundation model research community.Requirements:Master’s degree in Computer Science, Data Science, or a related technical field (PhD strongly preferred)Experience collecting and curating high-quality text data including multi-lingual data.Hands-on experience with large-scale dataset curation and preprocessing for ML/LLM training.Prior works synthesizing complex datasets. Code, math, and agentic data are higher priorityExperience with ML infrastructure for scalable training, evaluation, and debugging.Experience at the intersection of data and post-training (RL/SFT)Proven ability to independently drive research questions related to data quality, scaling, or reasoning.Preferred Experience: Experience with retrieval-augmented generation (RAG), agentic data pipelines, or reasoning benchmarks.Contributions to speculative decoding, self-curation, or reinforcement learning from synthetic data.Background in knowledge graphs, semantic search, or indexing systems.Strong publication record in leading AI conferences.Prior contributions to open-source ML data tools or benchmarks.Prior work on speculative decoding/contributions to LLM serving enginesPrior work on training LLM-as-a-judge Deep expertise with tokenization/training tokenizersWhy apply:Opportunity to build out a new division at the forefront of AI innovationFAANG competitive salary & packageWork alongside superstars from FAANG labs & leading AI companiesMedical, Dental and Vision InsuranceRelocation package available🌎 San Francisco Bay Area, USA📧 Interested in applying? Please click on the ‘Easy Apply’ button or alternatively email me your resume at stefani.lukic@storm3.com