Electrical / Information Engineer - Signal Processing & AI (m/f/d)

Job description

ATMOS Space Cargo is seeking a highly motivated Electrical or Information Engineer with a strong background in signal processing, audio data analysis, and neural networks.
In this role, you will be responsible for the design, development, and validation of AI-based systems for the detection, classification, and interpretation of acoustic signals. Your work will directly contribute to intelligent sensing, autonomy, and situational awareness in high-performance environments.
You will work at the intersection of signal processing, embedded systems, and machine learning, transforming raw acoustic data into reliable, actionable information.

Key Responsibilities:
- Design and implement signal processing pipelines for acoustic and audio sensor data (filtering, feature extraction, preprocessing)
- Develop and train neural networks for audio-based classification, detection, and pattern recognition (e.g. CNNs, RNNs, YOLO)
- Design and development of PCBs for signal processing and embedded systems
- Convert raw microphone and sensor data into meaningful representations (FFT, STFT, Mel-spectrograms)
- Implement and optimize AI models for real-time or near-real-time processing, including resource-constrained or embedded environments
- Support the integration of signal processing and AI algorithms into larger system architectures
- Conduct testing, validation, and performance evaluation of audio-based AI models under realistic and adverse conditions
- Collaborate with mechanical, electronics, and systems engineers to ensure proper sensor placement, data quality, and system integration
- Document algorithms, data pipelines, training procedures, and test results in accordance with engineering and quality standards
- Continuously improve robustness, accuracy, and efficiency of acoustic AI models

Profile required

- Bachelor’s or Master’s degree in Electrical Engineering, Information Technology or a related field
- 3+ years of experience in signal processing, data analysis, or machine learning
- Skilled in PCB Design Tools (Kicad, Altium or eagle)
- Strong knowledge of digital signal processing (DSP), especially for audio or acoustic signals
- Practical experience with neural networks and machine learning, preferably for time-series or audio data
- Proficiency in Python and common ML/DSP libraries (e.g. NumPy, SciPy, PyTorch, TensorFlow)
- Experience with feature extraction techniques for audio signals (FFT, MFCC, spectrograms)
- Understanding of sensor systems and data acquisition chains
- Excellent communication skills in English and German
- Analytical mindset, structured working style, and strong problem-solving skills
For this role, we can only consider applicants who already hold a valid right to work in the EU.

Preferred Qualifications:
- Experience with embedded AI, edge devices, or real-time signal processing
- Knowledge of microphone arrays, beamforming, or spatial audio processing
- Background in aerospace, robotics, automotive, or defense-related systems
- Experience with dataset creation, labeling, and augmentation for audio-based ML models
- Familiarity with software deployment pipelines and model optimization techniques

Company description

ATMOS was founded as a European company built on the values of freedom, democracy, equality, the rule of law, and human rights. We are committed to protect these values by making our technology available to others who share the same values, strengthening infrastructure and innovation for prosperity on Earth.
Our team is multinational and diverse, with offices in Lichtenau and Strasbourg. We work in a collegial, hands-on culture where people support each other, take ownership, and keep learning every day. Motivation for the mission comes first — building spacecraft is not a nine-to-five pursuit. We align the mission, the team, and the individual in mutual dependence. This principle shapes our work environment where exceptional people, as committed as they are competent, can grow and contribute to a mission that matters.

Job offer published on 1/16/2026