Job Specifications
Research Scientist - Data focus
Foundation Models, AI Research Institute
San Francisco Bay Area, USA
$200,000 - $350,000 salary + bonus
Come 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 priority
Experience 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 engines
Prior work on training LLM-as-a-judge
Deep expertise with tokenization/training tokenizers
Why apply:
Opportunity to build out a new division at the forefront of AI innovation
FAANG competitive salary & package
Work alongside superstars from FAANG labs & leading AI companies
Medical, Dental and Vision Insurance
Relocation 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
About the Company
Storm3 are specialists in US HealthTech recruitment, connecting organisations with the talent to drive their mission. Launched in 2020 to service the HealthTech industry, Storm3 connect senior talent with businesses at the forefront of healthcare technology innovation. Storm3 focus on placing talent into start up and scale ups across the United States. The pandemic has seen the HealthTech industry skyrocket with the uptake of new digital technologies, big data analytics and sophisticated AI. From genomics, telemedicine, FemT...
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