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

As a Computer Vision Intern, you'll work hands-on with our perception stack to build real-time detection, tracking, and scene understanding for outdoor security robots operating in unconstrained environments. You'll ship code that runs in the field and learn how to take research-grade CV into production on real hardware.

This role is highly practical: you'll help train models, build data pipelines, evaluate against field data, and integrate detectors into our autonomy stack. You'll get hands-on experience with the messy edge cases that distinguish lab demos from systems that actually work outdoors.

What You'll Work On

• Train, evaluate, and deploy object detection and tracking models for outdoor security scenarios.
• Build data pipelines that turn field-captured video into labeled training datasets.
• Run experiments on edge cases: low light, motion blur, weather, occlusion.
• Optimize models for edge deployment: quantization, pruning, latency tuning.
• Contribute to ROS 2 integrations and the wider autonomy pipeline.
• Apply solid engineering practices: Docker, version control, reproducible experiments.

Who We're Looking For

We're looking for a motivated computer vision student excited to apply academic training in a fast-moving startup. You'll be surrounded by a team that values learning, experimentation, and building things that actually work in the real world.

Your Background:

• Currently pursuing or recently completed a Master's degree in Computer Vision, Machine Learning, Robotics, or a closely related field.
• Strong PyTorch (or JAX) skills, with experience training and evaluating CV models.
• Familiarity with modern object detection and tracking architectures.
• Comfortable using Docker and Git in your workflows.