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Field Robotics Engineer – Data Operations (all genders

in 80331, München, Bayern, Deutschland
Unternehmen: Stark Defence
Vollzeit position
Verfasst am 2026-08-07
Berufliche Spezialisierung:
  • Software Entwicklung
    Robotik, Künstliche Intelligenz Ingenieur, Eingebettete Software ingenieur
Gehalts-/Lohnspanne oder Branchenbenchmark: 70000 - 100000 EUR pro Jahr EUR 70000.00 100000.00 YEAR
Stellenbeschreibung
Stellenbezeichnung: Field Robotics Engineer – Data Operations (all genders)

About Us

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.

About the team

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.

Your mission

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.

Responsibilities
  • 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

Qualifications
  • 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…

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