Our Mission
At 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 Role
You will be the first engineer on our Simulation team. Every site we map becomes a digital twin, built from our own lidar maps, and in it our robots see thousands of the intrusions, fires and sensor failures a real site sees once a year. Our multi-robot patrol policy was trained in simulation in under two hours on a single GPU and ran unmodified on real robots at three sites. Your job is to make that repeatable for every site and every new skill.
You will work with our Skills & Orchestration engineers, who train learned skills with reinforcement learning, and with our Reliability & Test Infrastructure engineer, who runs regression in the same simulator.
What You'll Work On
Map to twin: a pipeline from our lidar maps to simulation-ready digital twins: geometry, semantics, materials, sensors.
Training environments: RL environments for learned skills such as multi-robot patrol and search, randomised so nothing overfits one site.
Rare events: generate the scenarios real sites rarely produce: intrusions, sabotage, weather, sensor failures.
Sensor simulation: RGB, thermal and lidar realistic enough that what is learned in the twin holds on the robot.
Sim-to-real: measure the gap on real deployments and close it.
Scale: many parallel environments on GPUs, fast enough that a new skill trains in hours.
Who We're Looking For
A simulation engineer who treats the simulator as production infrastructure and measures success by what transfers to real robots.
Your Background
3+ years building robotics simulation or RL training environments.
Hands-on with Isaac Sim or Isaac Lab; MuJoCo or Gazebo also considered.
Strong Python; C++ a plus.
3D data: point clouds, meshes, scene formats such as USD.
GPU-parallel simulation and reinforcement learning workflows.
Nice to Have
Legged robots.
Photogrammetry, Gaussian splatting or other scene reconstruction.
ROS 2.
Thermal or lidar sensor modelling.
What We Offer
Ownership: you are able to ship products and deliver project end-to-end.
Mission: autonomous security that keeps people and critical sites safe, including in defence.
Career path: a ground-floor seat with real runway. Prove your value and you will not have barriers to grow.
Team: work directly with PhD-level co-founders in AI, Robotics, and Physics, alongside a strong (and fun) founding team.
Compensation: Competitive equity/salary package
Culture: International founding team that is serious about building but does not take itself too seriously.