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NeuralAgent

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Senior Embedded Systems Engineer

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You'll join a company where your work has visible impact from day one.
You'll work directly with world-class engineers, scientists, aerospace experts and entrepreneurs building technologies that have never existed before.
Every day you'll collaborate with people who genuinely believe Europe can lead the next generation of autonomous intelligence.
We're not maintaining legacy systems.
We're creating the infrastructure future generations will depend on.

What We Offer
Competitive compensation
Relocation support
Individual learning budget
Modern aerospace campus with an on-site canteen and gym
Free beverages
Lunch support
Tax-free employee benefits
Flexible working hours
Regular remote work
30 days of vacation

Join Us
If you're ready to build technology that could shape Europe for decades to come, we'd love to meet you As a Senior Embedded Systems Engineer, you are the bridge between our edge AI operating layer and the real-world hardware it runs on. You’ll work with a defined, proven system rather than starting from scratch, and help extend it with embedded agent and edge AI capabilities that let autonomous systems think and act on-device.

In this role, you will:
  • Deploy our Rust-based edge stack across drones, ground and maritime robots
  • Build embedded agent and edge AI capabilities for low-power hardware
  • Lead hardware bring-up and multi-sensor integration (IMUs, cameras, LiDAR)
  • Support customer deployments and turn field feedback into improvements
Must have
  • Master's degree or PhD in Computer Science, Engineering or a related field.
  • Minimum of 5 years work experience in a company
  • Proficiency in Python and first experience deploying Rust in production
  • Proven experience adapting and deploying embedded systems across diverse hardware targets and customer environments
  • Deep experience with low-power edge compute as the primary control layer for autonomous or robotic systems
  • Comfortable working with multi-sensor data (IMUs, cameras, LiDAR) and assessing hardware constraints quickly to make pragmatic adaptation decisions
  • Prior experience in robotics, UAV, or aerospace contexts strongly preferred
  • Excellent communication skills in English; German language skills are a plus.
Nice to have
  • Deploying ML models on edge devices (e.g. ONNX, TensorRT)
  • ROS 2, embedded Linux or real-time operating systems
  • Edge AI platforms such as NVIDIA Jetson
  • Protocols such as CAN, MAVLink, UART or SPI

Skills

What Senior Embedded jobs ask for — and how much of it you have →
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See also

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