Research Engineer - Data Eval

Calder collects, curates, and quality-evaluates real-world and egocentric capture data used to train world models and robotic foundation models. Data quality is our core differentiator, and this role owns the measurement loop that proves it — from raw capture all the way to downstream model impact.

You move fast and take ownership, turning recent papers into prototypes and tools that run at scale on real sensor and trajectory data. You lead technically, mentor naturally, and partner well across research, robotics, engineering, and product. You communicate clearly, document thoroughly, and thrive in the ambiguity and pace of an early-stage company.

You should be comfortable with the ML experimentation stack (PyTorch, training/eval infrastructure, open-source model ecosystems), rigorous about experimental design, and skeptical by instinct. Experience with robotics, imitation learning, world models, computer vision models, or large-scale data pipelines is a strong plus.