(Senior) Robotics AI Engineer

(Senior) Robotics AI Engineer

Agile Robots

Munich, Germany

About the role

The AI Research Division of Agile Robots is looking for experienced robotics engineers who build AI-enabled robotic systems that work in the real world. In this role, your primary responsibility is to design, integrate, and operate robotic systems that use machine-learning models under real-world constraints such as latency, safety, sensing noise, and hardware variability. You will work closely with ML Research Engineers and ensure that ML-driven capabilities survive contact with real robots and behave reliably in practice.

Your Responsibilities

(Your exact scope depends on your background and team alignment.)

• System Integration: Design and implement robotics software that integrates ML model inference into perception, decision-making, and action pipelines on real robotic platforms.
• Runtime Reliability: Ensure stable system behavior by handling latency, synchronization, safety constraints, and failure modes in real-world operation.
• Embodied Sensing: Work with robot sensors and signals such as cameras, depth, proprioception, and other modalities to enable robust perception and interaction.
• Operational Debugging: Diagnose and resolve system-level issues across software, sensing, hardware interfaces, and runtime execution.
• Data Capture: Build and maintain data collection, logging, and validation workflows from robot runs, teleoperation, or simulation.
• Simulation Testing: Use simulation and testing frameworks to validate behaviors, reduce deployment risk, and reproduce real-world failures.
• Cross Teamwork: Partner as a peer with ML Research Engineers, data engineers, and control engineers to align models with real-world constraints.

Essential Skills

• Education Level: Bachelor's or Master's degree in a relevant field, along with several years of relevant practical experience in robotics systems engineering.
• Robotics Software: Solid experience developing software for robotic systems or autonomous platforms.
• Systems Coding: Strong programming skills in Python and/or C++.
• Middleware Use: Experience working with robotics middleware, sensing systems, and runtime integration.
• System Constraints: Understanding of real-world robotics constraints including latency, synchronization, safety, and hardware variability.
• Operational Depth: Proven ability to debug, test, and operate robotic systems beyond simulation.

Beneficial Skills

• ML Integration: Experience integrating ML inference into robotics systems for perception, action selection, or policy execution.
• ROS Experience: Familiarity with ROS2 or similar robotics frameworks.
• Embodied Data: Exposure to teleoperation, simulation, or embodied data collection workflows.
• Multimodal Signals: Experience working with robot data such as vision, depth, force, or trajectories.
• AI Curiosity: Strong interest in AI-enabled robotics and embodied intelligence.