Research Engineer, Data Foundations
Remote$270k - $370kFull-timePosted 3mo ago
About the role
Role focused on designing and curating large-scale multimodal data to train world models, build data pipelines for synthetic data generation and quality control, and define evaluations that measure real improvements in model capabilities.
Responsibilities
- Design multimodal, multitask datasets that teach world models new capabilities — deciding what data to collect, generate, or curate and measuring its effect on model behavior
- Run controlled training experiments to understand how data composition drives model performance across tasks and domains
- Build and operate large-scale pipelines for synthetic data generation, filtering, and quality control
- Define evaluations and benchmarks that measure whether our models are actually improving at the things that matter
- Partner with product and creative teams to translate target behaviors and capabilities into concrete data strategies
Qualifications
- 4+ years of experience in machine learning, bonus points for data-centric approaches
- Experience with large multimodal datasets and generative models (video, image, or multimodal)
- Deep intuition for how data composition and quality translate to model capabilities
- Comfort working across the full research stack: data analysis, dataset creation, model training, evaluation, and back again
- Proficiency with at least one ML framework (e.g. PyTorch, JAX) and distributed compute tools (e.g. Ray, Kubernetes)
- Excitement about building AI that simulates the world
Skills
Required:Multimodal data designData-centric MLExperimentation and benchmarkingDataset creation and data pipelinesML frameworks
Last updated Oct 25, 2026. Interested? Apply on the company site.
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