AI Software Engineer, Stimulation (f/m/d)
Tactiliarobotics · Munich
What this role requires
7 requirements, read out of the advert rather than guessed from the job title:
Also mentioned, not required: physics engines, reinforcement learning, imitation learning, MuJoCo, Isaac Sim, Isaac Lab. Worth having, but their absence is not what gets a CV filtered out.
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Job description
About TACTILIA
At TACTILIA, we are building the industry-ready robotic hand that closes one of the biggest gaps in Physical AI. Spun out of SCHUNK, the global market leader in gripping technology, we combine a decade of robotic-hand expertise and real industrial access with the speed and ambition of a deep-tech startup.
This isn't a research project waiting for its first customer. We already have a product, customers are ready to use it, and we are launching now. Your work will directly shape the electronics, actuators, and embedded systems that make that possible.
You will join at the moment when the hard engineering questions become real product decisions: how do we make a highly capable robotic hand reliable, manufacturable, serviceable, and simple enough to deploy on a real shop floor?
The Role:
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.
Read the full description (31 more sections)Show less
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
What you bring:
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
The next chapter of robotics won't be built in a lab. It will be built by people who care about what happens when technology meets the real world.
At TACTILIA, you'll work on one of the hardest open problems in robotics: giving machines the dexterity, reliability and robustness to interact with the physical world at industrial scale.
The technology is taking shape, the team is being built, and the standards around robotic hands and their skills are still open. That means your decisions will have a lasting impact — not just on a product, but on what comes next for Physical AI.
Build the hand. Define the standard. Shape what comes next.
If you're excited by the challenge of building robotic hands that works reliably in the real world, we'd love to hear from you.
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