Software Engineer, Robot Autonomy (Multi Robot Orchestration), Intern

Startupvalleys; Zürich; Hybrid; CHF 28,000 - 45,000; Part time

Benefits offered by this job

Ownership of projects

Competitive equity/salary package

International team

Job summary

Laelaps AI in Zürich seeks a Software Engineering Intern to advance multi-agent orchestration for autonomous security robots. You will design and evaluate MARL algorithms, explore decentralized task allocation, and improve simulations for real-world deployment.

The role offers close collaboration with PhD-level founders, a fast-paced startup environment, and opportunities to ship practical software while learning cutting-edge AI and robotics techniques.

Qualifications

• Pursuing or completed Master’s/PhD in CS, robotics, AI.
• Hands-on RL experience via projects.
• Experience with simulators Isaac Sim, MuJoCo, Gazebo.

Responsibilities

• Design and evaluate MARL algorithms for multi-robot surveillance.
• Develop decentralized coordination strategies and task allocation.
• Implement simulations and deploy on real robots when possible.
• Benchmark performance and robustness in dynamic environments.

Skills

Reinforcement Learning

Robotics

Python

Education

Master's degree in Computer Science / Robotics / AI

PhD (preferred)

Tools

PyTorch

JAX

ROS 2

Job description

Software Engineer, Robot Autonomy (Multi Robot Orchestration), Intern at Laelaps AI · Startup Valleysstartupvalleys.comMapCompaniesJobsValleysGet featuredManage companySign inSoftware Engineer, Robot Autonomy (Multi Robot Orchestration), Internat Laelaps AIApplyAll rolesNext rolePosted 29 Oct 2026Laelaps AI Zürich, Switzerland · MapApply# Software Engineer, Robot Autonomy (Multi Robot Orchestration), InternEngineeringOriginal posting — from Laelaps AIOpen original#### 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 RoleAs a Software Engineering Intern in Multi-Agent Orchestration, you'll work on developing the orchestration layer that enables our autonomous agents to coordinate, collaborate, and make intelligent decisions to achieve efficient and scalable surveillance. Your primary focus will be on Multi-Agent Reinforcement Learning (MARL), exploring how agents can learn optimal coordination strategies in dynamic environments. You'll also have the opportunity to explore alternative approaches, including task allocation algorithms, decentralized planning, and optimization techniques, to build robust and adaptive multi-agent systems.This role is highly practical as we expect the developed methodologies not only to work I. simulation, but be deployed in real world scenarios.#### What You'll Work On* **Multi-Agent Reinforcement Learning:** Design, train, and evaluate MARL algorithms for cooperative multi-robot surveillance and persistent patrolling.* **Multi-Robot Coordination:** Develop strategies for decentralized decision-making, task allocation, and efficient collaboration between autonomous robots.* **Simulation:** Improve our simulations to train the policies that can be later transferred to the real world.* **Real-World Deployment:** Build and test algorithms in simulation environments, with opportunities to deploy them on real quadruped robots.* **Algorithm Research & Optimization:** Explore and compare learning-based approaches with classical optimization, planning, and heuristic methods.* **Performance Evaluation:** Develop benchmarks to assess surveillance coverage, patrol efficiency, scalability, and robustness in dynamic environments.#### Who We're Looking ForWe're looking for a motivated robotics or machine learning 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 in the final stages of a Master's degree or pursuing a PhD in Computer Science, Robotics, Artificial Intelligence, or a related field.* Demonstrated hands-on experience with Reinforcement Learning, backed by academic, personal, or research projects.* Experience with robotics simulators such as Isaac Sim, MuJoCo, or Gazebo or custom built simulators.* Solid understanding of reinforcement learning algorithms and concepts.* Ability to independently research, implement, and evaluate algorithms.* Good coding skills in Python, with PyTorch (or JAX).#### Nice to Have* Experience deploying learned policies on physical robots, ideally legged.* C++ and ROS 2 experience.* Publications at top robotics or ML venues (CoRL, RSS, ICRA, NeurIPS).#### 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.This provider only shows the posting on its own website.