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 VLA/VLM Intern, you'll research and apply foundation models for robot control, contextual reasoning, and natural language interaction. You'll work at the frontier of embodied AI, taking state-of-the-art VLA and VLM research and pushing it toward real deployment on physical robots.

This role is highly practical: you'll run experiments, build data pipelines, fine-tune large models, and contribute to the systems that get them running on real hardware. You'll get exposure to the gap between SOTA papers and what actually works when a robot needs to act in the real world.

What You'll Work On

• Run experiments with VLA/VLM models for robot control and scene understanding.
• Build data pipelines for fine-tuning foundation models on robotics tasks.
• Evaluate models against real-world tasks and edge cases.
• Contribute to the integration of learned components with classical autonomy modules.
• Optimize models for edge deployment: quantization, distillation, latency tuning.
• Apply solid engineering practices: experiment tracking, reproducibility, evaluation discipline.

Who We're Looking For

We're looking for a motivated 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 PhD or recently completed a Master's degree in Machine Learning, Robotics, Computer Vision, or a closely related field.
• Strong PyTorch (or JAX) skills, with experience training or fine-tuning large models.
• Familiarity with the current VLA/VLM landscape (π0.5, GR00T, or similar).
• Good coding skills in Python.