> Markdown version of [/jobs/ext/1247544-research-engineer-sim-to-real-robot-learning-infrastructure](https://www.wearedevelopers.com/jobs/ext/1247544-research-engineer-sim-to-real-robot-learning-infrastructure). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Research Engineer - Sim-to-Real & Robot Learning Infrastructure

- **Company:** OMN4I Robotics
- **Location:** München, Germany
- **Contract:** Permanent contract
- **Skills:** Software Debugging, Machine Learning, Software Engineering, Reinforcement Learning, Data Logging, Machine Learning Operations, Data Pipelines
- **Published:** July 12, 2026
- **Apply:** https://de.indeed.com/viewjob?jk=e5bd965bf2d450a3

## About the Role

_ Strong software engineering background with real experience in robotics, ML infrastructure, or simulation systems. _ Hands-on experience with at least one of: ROS/ROS2, robot simulation (Isaac Sim, MuJoCo, or similar), or large-scale ML training infrastructure. _ Comfortable working close to real hardware - debugging when something breaks on an actual robot, not just in simulation. _ Can move between "quick and dirty prototype" and "this needs to be reliable" depending on what the moment calls for., _ Experience with reinforcement learning pipelines specifically (not just supervised/imitation training infra). _ Background in sim-to-real transfer research or robot learning benchmarks. _ Experience standing up ML infrastructure at a very early-stage team (few or no existing systems to build on). _ Familiarity with physics simulators beyond a single ecosystem.

## Description

_ Build and maintain the data pipeline connecting real robot rollouts to training infrastructure. _ Own sim-to-real transfer - closing the gap between simulated training and real hardware performance. _ Build tooling for large-scale training experiments: logging, evaluation harnesses, reproducibility, fast iteration loops. _ Work closely with our research scientists to translate architecture and algorithm ideas into running systems. _ Help shape engineering standards as one of the first hires - there's no legacy codebase to inherit or work around.


## Related Videos

- [Robots are coming into the wild! Full-Stack Robotics Engineers, be ready!](https://www.wearedevelopers.com/videos/479-robots-are-coming-into-the-wild-full-stack-robotics-engineers-be-ready)
- [Crypto-secure Data Management with In-Database Blockchain](https://www.wearedevelopers.com/videos/632-crypto-secure-data-management-with-in-database-blockchain)
- [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning)
- [Why and when should we consider Stream Processing frameworks in our solutions](https://www.wearedevelopers.com/videos/1085-why-and-when-should-we-consider-stream-processing-frameworks-in-our-solutions)
- [What non-automotive Machine Learning projects can learn from automotive Machine Learning projects](https://www.wearedevelopers.com/videos/397-what-non-automotive-machine-learning-projects-can-learn-from-automotive-machine-learning-projects)
- [How Machine Learning is turning the Automotive Industry upside down](https://www.wearedevelopers.com/videos/61-how-machine-learning-is-turning-the-automotive-industry-upside-down)

## Related Articles

- [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it)
- [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer)
- [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production)
- [How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again](https://www.wearedevelopers.com/magazine/751-how-we-built-a-worry-free-system-that-runs-for-10-years-and-what-we-d-do-again)
- [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline)
- [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)