Field Robotics Engineer – Data Operations (all genders)
At a glance
Mid-level Data Architecture & Governance role at Stark. Munich · full-time.
Pay not stated Data Architecture & Governance salary
dataroles summary, based on the employer's posting.
What you'll do
- Connect cameras, gimbals, lidar, radar, IMUs and GNSS from their electrical links through to complete recording workflows
- Write sensor drivers and ROS2 components that communicate over the hardware interfaces used by the equipment
- Align sensor timing and calibrate camera and IMU setups so recordings can be combined accurately
- Build Jetson recording pipelines, then test sensor performance and resolve issues during field campaigns across Europe
- Document integrations and calibration results so teammates can reproduce each setup
What you bring
- A robotics, mechatronics, electrical engineering or computer science degree, or comparable practical experience
- Working Python and C++ skills, with ROS2 experience on physical systems
- Practical sensor integration on embedded Linux and familiarity with several hardware communication protocols
- Knowledge of camera geometry, OpenCV, coordinate transforms and distributed-system time alignment
Who this fits
This role suits a hands-on engineer who works across hardware and software and can troubleshoot recording systems in the field. You should be willing to travel regularly across Europe and work outdoors in varied conditions. The team considers candidates across experience levels and adjusts the scope and seniority to their background.
From the employer
STARK is a new kind of defence technology company revolutionizing the way autonomous systems are deployed across multiple domains. We design, develop and manufacture high-performance unmanned systems that are software-defined, mass-scalable, and cost-effective. This provides our operators with a decisive edge in highly contested environments.
We're focused on delivering deployable, high-performance systems — not future promises. In a time of rising threats, STARK is bolstering the technological edge of NATO Allies and their Partners to deter aggression and defend Europe — today.
The Data Operations team owns the entire data lifecycle behind STARK's AI stack: collection, acquisition, generation, curation, and management. We run our own data-collection campaigns across Europe, evaluate new sensors and platforms, and build the internal data platform that turns raw recordings into ready-to-use datasets. Everything we produce feeds directly into the perception and autonomy systems deployed on STARK's platforms — a real data advantage is built, not bought. The team is scaling up right now: real scope, direct impact, no legacy.
You are the technical owner of our multi-sensor recording systems — the bridge between raw hardware and the datasets our ML teams train on. You work at the critical intersection of hardware and software: integrating EO/IR cameras, lidar, radar, and IMUs over their real interfaces, adapting the drivers and ROS2 nodes that capture them, solving time synchronization down to the microsecond, and calibrating multi-sensor rigs so every stream is spatially and temporally unified. And you don't just build in the lab: you regularly join our data-collection campaigns across Europe, deploying your systems under real conditions and making sure the data we bring home is worth training on.
Own the end-to-end integration of our sensor suites — EO/IR cameras, gimbals, lidar, radar, IMU, GNSS — from electrical interfaces and wiring to working recording pipelines
Design and implement sensor drivers and ROS2 nodes, working directly with hardware protocols including I2C, SPI, CAN, Serial, MIPI/CSI-2, GigE Vision, and Ethernet (RTSP/UDP)
Solve temporal synchronization across distributed sensors (PTP, PPS, hardware triggering) so all streams are perfectly aligned for fusion and labeling
Develop and execute rigorous intrinsic and extrinsic calibration routines (camera-camera, camera-IMU) to spatially unify the sensor rigs
Build and optimize the onboard recording stack on embedded compute (NVIDIA Jetson): hardware-accelerated video pipelines (GStreamer), efficient logging (MCAP/rosbag), and storage throughput under compute, thermal, and bandwidth constraints
Evaluate new sensors hands-on at the bench — from probing electrical interfaces with diagnostic tools to benchmarking SDKs — and turn results into clear integration decisions
Join field data-collection campaigns across Europe: prepare and verify sensor setups, operate the recording systems on-site, diagnose hardware and software issues in real time, and validate recordings before leaving the site
Produce integration documentation and calibration reports so every setup is reproducible by the team
Degree in Robotics, Mechatronics, Electrical Engineering, Computer Science, or comparable practical experience
Proficiency in Python and C++ for robotics and hardware interfacing
Experience with ROS2, including deployment on physical systems
Hands-on experience with several hardware protocols such as I2C, SPI, CAN, Serial, or Ethernet-based sensor communication
Experience integrating cameras or other sensors on embedded Linux platforms, ideally NVIDIA Jetson
Solid computer vision fundamentals: camera models, distortion, projection geometry, OpenCV
Good understanding of coordinate frames, transformations, and time synchronization in distributed systems — practical calibration experience is a strong plus
Comfortable with hardware diagnostic tools (multimeter, oscilloscope) as well as modern software workflows (Git, CI, Docker)
Practical and structured; willingness to travel regularly for field campaigns and to work outdoors in various conditions
UAV or mobile robot experience; PX4/ArduPilot and MAVLink basics
Photogrammetry + 3D Reconstruction
Low-level driver development or customization on embedded Linux
GStreamer hardware-accelerated pipelines, JetPack/L4T, CUDA/TensorRT
MIPI/CSI-2 camera bring-up, ISP tuning, or Linux kernel/device tree exposure
Calibration tooling such as Kalibr; lidar and point cloud processing (PCL, Open3D)
Experience with detection/tracking models and modern CV pipelines (PyTorch, ONNX)
Experience with simulation (Gazebo, Isaac Sim) or synthetic data generation
We hire this role across experience levels: whether you bring a few years of hands-on robotics work or a decade of sensor integration, we will match scope and seniority to your profile.
A note on our process: we value critical thinking, grit, and the ability to learn over a perfect checklist. If you are a talented engineer who loves building complex systems at the boundary of hardware and code, but you don't hit every single bullet point, we still want to hear from you.
If you're interested in building the future of European Defence with us, and you see yourself reflected in the description above, please send us your CV in English. We're looking forward to meeting you!