Our MissionAt Laelaps AI, we believe robotics is entering a transformative decade, much like the arrival of the internet.
Advances in AI, cloud computing, and hardware are reshaping what autonomous systems can do.
Our mission is to build the intelligent software that powers physical security in the real world - enabling robots and sensors to handle dangerous and critical tasks that humans shouldn't have to.
By engineering the orchestration layer for intelligent security, we aim to create a world that is safer, more secure, and more resilient.
We're a strong founding team based in Zurich, backed by visionary investors and advisors.
We are engineering the future of security today!The RoleYou will own the research question at the centre of LEA, our foundation model of the physical world: can a model learn what normally happens on a site, by place, hour and weather, so that an anomaly is simply what it did not expect? The first version is a probabilistic memory of each site.
The next is a world model across every site that predicts the next state in latent space, starting from open world-model weights and growing on field data nobody else holds.
Our robots and cameras run on live security sites around the clock, and every event is kept with its clip, the model's verdict and the operator's outcome.
That record is your dataset.
You will work alongside our perception and model engineers, and your results go into production, not only into papers.
What You'll Work OnSite memory: a learned, probabilistic model of each site: which people, vehicles and robots are where, at what hour, in what weather, and how the scene usually unfolds.
Anomaly as surprise: replace rule-based alerting with measured surprise, and work out how to evaluate it when real incidents are rare.
World model: post-train open world-model weights on aligned multi-sensor field sequences, JEPA-style, predicting in latent space rather than pixels.
Transfer: from one site's memory to a model of all of them, and repr.