Machine Learning Engineer (Robotics)

TL;DR

Machine Learning Engineer (Robotics): Developing and deploying machine learning models with a focus on deep learning, reinforcement learning, and simulation-to-reality (sim2real) transfer for real-world robotics and control systems. Focus on building intelligent systems that learn in simulation and perform in the real world.

Location: Remote within a similar time zone to Zurich, Milan, and Rome.

Company

Cyberwave's vision is to unlock the full potential of intelligent machines by making robotics as accessible, scalable, and programmable as cloud software.

What you will do

• Architect and optimize C++ core systems supporting real-time interaction between simulated and physical environments.
• Build and maintain infrastructure for data ingestion, synchronization, and transformation across diverse hardware and simulation platforms.
• Develop high-performance simulation and digital twin software, leveraging modern environments such as MuJoCo, Isaac Sim, or Newton.
• Design modular APIs that abstract simulator-specific complexity and integrate with learning and control pipelines.
• Contribute to sim-to-real workflows, including environment randomization, configuration management, and scenario generation.

Requirements

• Degree in Robotics, Computer Science, Electrical Engineering, Physics, or a related field (BSc/MSc/PhD), with a strong foundation in applied control engineering, computational modeling, mathematics, or physics.
• 5+ years of experience developing production-grade software in C++, with a focus on performance, memory management, and maintainability.
• Hands-on experience with real robots including setup, customization, and integration with other systems.
• Deep familiarity with robotics middleware, such as ROS or ROS 2.
• Practical experience with physics-based simulators (e.g., MuJoCo, Isaac Sim, Newton, Gazebo) and hands-on work with robotic hardware or embedded platforms.
• Strong understanding of real-time systems, concurrency, and multi-threaded programming.

Nice to have

• Background in numerical methods, computational geometry, or game engine physics is a strong plus.
• Prior experience in startups, R&D labs, or environments requiring rapid prototyping and deployment.

Culture & Benefits

• Work on high-impact robotics problems, enabling the next generation of intelligent machines.
• Join a world-class, cross-disciplinary team that values innovation, curiosity, and bold thinking.
• Flexible work culture with support for remote work and autonomy over your schedule—outcomes over hours.
• Access to state-of-the-art simulation environments and robotic systems, from digital twins to physical platforms.