You'll join a team that trains, tests, and deploys AI on real humanoid robots every single day, and you'll own the invisible infrastructure that makes all of it feel effortless. Expect a playground of GPUs, self-hosted runners, simulation clusters, and pipelines that stretch from a git push all the way onto a robot standing in our lab.
CI/CD Engineering: Shape our pipelines across GitLab and GitHub Actions, matrix builds, smart caching, multi-stage workflows for robotics code and ML training jobs.
Infrastructure as Code: Tame our fleet of runners, GPU workstations, and lab machines with Ansible, so "it works on my machine" becomes "it works on all of them".
Python Packaging & Tooling: Turn internal libraries and controllers into clean, versioned pip-installable packages with uv, and help design how we host and consume them internally.
Containers Everywhere: Build and optimize Docker images (yes, including the fun DinD / DooD rabbit holes) for training, simulation, and deployment — fast, small, reproducible.
Simulation at Scale (Isaac Sim): Bring NVIDIA Isaac Sim / Isaac Lab into CI: headless simulation containers, scenario- and policy-level regression tests, and a safety net that catches bugs before they meet real hardware.
Deployment Pipelines: Ship validated artifacts, Python packages, Docker images, model checkpoints, sim assets, from CI all the way onto lab machines and physical robots, with rollbacks that actually work.
Nightly Runs: Own the heartbeat of the team: nightly training, evaluation, simulation, and integration runs. Schedule them, watch them, triage them, make them better.
Git & Repo Hygiene: Help us stay sane with submodules, LFS, code owners, protected branches, and no more 2GB accidental commits.
Currently pursuing or recently completed a degree in Computer Science, Software Engineering, Electrical Engineering, or a related field.
Solid proficiency in Python, plus comfort with Bash and Linux command-line tooling.
Hands-on experience (from studies, side projects, or previous internships) with at least some of: Docker, GitLab CI, GitHub Actions, Ansible, uv/pip, Git submodules & LFS.
Bonus: exposure to NVIDIA Isaac Sim / Isaac Lab, ROS 2, headless GPU simulation in containers, or automated deployment to robots / edge devices.
Understanding of CI/CD concepts: caching, artifacts, runners, pipelines, reproducible builds.
Curiosity about MLOps and how to keep large ML/robotics training pipelines healthy and cost-efficient.
Strong problem-solving and debugging skills, you enjoy figuring out why a pipeline is red at 3am (figuratively).
You care about developer experience and want to make life easier for the engineers around you.
Your communication skills make you shine.
You have a good command of the English language and, ideally, also speak German.
