Senior Data Engineer, Simulation & Synthetic (m/f/d)

3 нед. назад

GermanyEuropeSenior

rosros2simulationlidardata-augmentationsynthetic-datasim2real

Senior Data Engineer responsible for creating synthetic simulation environments and data for autonomous off-road vehicles.

ARX is a dual-use technology company that specializes in developing autonomous unmanned systems and sensors for the European defence sector. Our dual-use unmanned ground systems and sensors assist NATO Armies and civilian first responders in tackling their most challenging problems by providing them with training and information to make better decisions and take effective actions in life-or-death situations. As our team continues to expand rapidly, we are seeking motivated candidates who are excited to work in a highly energetic, creative, and innovative team dedicated to developing autonomous systems for challenging environments. We operate in a dynamic sector where collaboration, sharing innovative ideas, and developing novel problem-solving strategies are ingrained in our work culture.
You can find ARX Robotics Applicant Privacy Policy  here .

As our Simulation & Synthetic Data Engineer, you’ll be at the heart of our autonomy stack, creating the virtual worlds that teach our robotic systems to navigate the real one. You will join a dedicated team developing cutting-edge autonomous ground vehicles, and your work will directly accelerate how our systems learn, adapt, and perform in the most demanding off-road environments. Your mission is to build the bridge between simulation and reality. By generating high-fidelity data and crafting complex scenarios, you will enable our perception and autonomy software to train, test, and validate at a speed and scale that would be impossible otherwise. This role is critical to advancing the capabilities and robustness of our autonomous platforms.

Strong proficiency in Python or C++ and hands-on experience with ROS2.
Proven experience developing simulation environments (e.g., Unity) with a solid foundation in computer graphics.
Deep familiarity with camera and LiDAR sensors and the process of generating synthetic data for them.
A strong understanding of Sim2Real methodologies and the challenges of transferring models from simulation to the real world.
A collaborative spirit with a proactive, results-oriented approach to solving complex technical challenges.
Bonus points for experience with machine learning frameworks (like TensorFlow) or sensor fusion techniques.
Please note: You do not need to meet every single requirement to apply. We welcome motivated candidates who are eager to grow into the role and develop their expertise further.

Join a mission-driven European defense tech company at a pivotal stage of growth, where you can help shape meaningful technology, take ownership early, and grow with the business!
Competitive compensation package including a bonus opportunity
27 vacation days to start, increasing with tenure up to 30 days
Employer-supported pension contribution
Learning & development support and team events budget
Employee discounts and flexible benefits budget via Probonio
Hybrid working setup depending on role and team needs
Structured salary bands, levelling framework, and bi-annual development conversations
Referral bonus program, dog-friendly office, and relocation support where applicable

Construct and expand rich, realistic simulation environments for our autonomous off-road vehicles.
Generate high-fidelity synthetic sensor data—from cameras to LiDAR—to train our perception algorithms.
Craft complex virtual scenarios, including dense forests, rugged terrain, and adverse weather, to push our systems to their limits.
Develop sophisticated data augmentation and domain randomization pipelines to ensure our models are robust and adaptable.
Implement and refine Sim2Real strategies, bridging the gap between virtual testing and real-world performance.
Integrate your simulation modules seamlessly with our ROS/ROS2-based robotics software stack.
Collaborate closely with our AI and robotics teams to continuously enhance synthetic data quality and accelerate model development.