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.

This posting serves as a broader entry point to our teams. After we evaluate your background, we’ll match you with the specific role and team where your skills have the most impact. The team assignment happens during the interview process.

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.

What we offer

Dynamic high-tech company combined with financial soundness and world class investors.
Join an interdisciplinary, international team with 60+ different nationalities in a collaborative work environment.
Lots of development opportunities in the context of our continued growth.
Challenging tasks and impactful projects alongside experts that enable professional and personal growth.
Corporate Benefits Program that covers health, mobility and learning with 100 € net per month.
Modern office facilites with a rooftop terrace overlooking Munich, free drinks & fruits, and regular company events contribute to a good working environment.

(Senior) Robotics AI Engineer (m/f/d)

TLDR

About the role

Your Responsibilities

Essential Skills

Beneficial Skills

What we offer

Benefits