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# AI Software Engineer, Stimulation

- **Company:** TACTILIA robotics
- **Location:** München, Germany
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, C++ (Programming Language), Python (Programming Language), Kinematics, Machine Learning, Microsoft Dynamics, Robotic Automation Software, Software Engineering, Software Systems, Reinforcement Learning, Delivery Pipeline, Information Technology
- **Published:** September 21, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=56a62c459047e971

## About the Role

* Degree in Computer Science, Robotics, AI, Electrical Engineering or a related field
 * Strong software engineering skills in Python and C++
 * Experience with robotics simulation and/or physics engines
 * Experience with machine learning applied to robotics
 * Good understanding of robot kinematics, dynamics and control
 * Experience working with robotic systems, sensors and/or simulation environments
 * Strong problem-solving skills and a pragmatic, hands-on approach
 * Ability to work across AI, software and physical robotics

Bonus:

 * Experience with reinforcement learning or imitation learning
 * Experience with simulation-to-real transfer
 * Experience with MuJoCo, Isaac Sim, Isaac Lab or similar simulation frameworks
 * Experience with dexterous manipulation, grasping or robotic hands

## Description

As an AI Software Engineer focused on Simulation, you will build the simulation and software infrastructure that enables TACTILIA's robotic hands to learn, test and improve before they touch the real world.

You will work at the intersection of robotics, simulation and AI - developing environments, models and tools for training and evaluating robotic hand behaviours. Your work will help bridge simulation and reality and accelerate the development of dexterous manipulation skills.

What you will do:

 * Build and maintain simulation environments for robotic hands and dexterous manipulation
 * Develop simulation models for robot dynamics, actuators, sensors and contact interactions
 * Develop software infrastructure for training, evaluating and benchmarking AI-based manipulation policies
 * Work with reinforcement learning, imitation learning and other learning-based approaches for robotics
 * Build pipelines for simulation-to-real transfer and validate policies on real robotic hardware
 * Generate and manage simulation data for training and evaluation
 * Integrate simulation environments with robotics and AI software stacks
 * Collaborate closely with robotics, controls and hardware engineers to translate real-world behaviour into simulation
 * Develop tools and workflows that make simulation faster, more reliable and useful for product development


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