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AI & Machine Learning Engineer – Sensor Fusion & Situational Awareness - 2279
Rheso.Tech
München · Hybrid €65k – €105k/yr 3w ago
About the role
AI & Machine Learning Engineer – Sensor Fusion & Situational Awareness (M/F)
- Contract type: Permanent
- Location: Greater Munich (Hybrid)
- Ref: 2279
- Contact: paul@rheso.tech
The recruiting company
Our client is a European start‑up specializing in electronic warfare, secure communications, and precision localization technologies for the defense sector.
Key points of the position
Reporting to the engineering team, you will develop advanced AI and machine learning algorithms that transform complex sensor data into reliable situational awareness for defense operations.
Responsibilities
- Processing and analyzing large volumes of real‑world sensor data collected in operational environments
- Designing, training, and optimizing machine learning models to classify signals and interpret complex, noisy data streams
- Developing advanced sensor fusion algorithms combining machine learning techniques with classical state estimation methods such as Kalman filters
- Translating ML prototypes into efficient algorithms deployable on embedded systems, in collaboration with embedded software teams
- Optimizing and quantizing ML models to run on resource‑constrained edge hardware
- Developing predictive models capable of anticipating environmental changes and entity movements
- Validating and improving algorithms using simulation environments and real‑world data from field tests
Necessary skills
- Degree in Computer Science, Machine Learning, Robotics, Physics, or a related field
- Proven experience in applied machine learning and sensor data processing
- Strong experience with modern ML frameworks such as PyTorch or TensorFlow
- Solid programming skills in Python and good proficiency in C++ for algorithm deployment on embedded systems
- Strong understanding of sensor fusion, tracking, and localization concepts
- Comfortable working with imperfect real‑world datasets and extracting meaningful insights from noisy inputs
- Fluent English is required; German is strongly appreciated
Eligibility
- Eligibility for German security clearance (SÜ2/Ü2) is required
- German or EU citizenship is mandatory
Salary
- 65–105 k euros gross annual
Recruiter
RHESO.TECH, a specialized recruitment agency
https://www.rheso.tech/
Keywords
machine learning, artificial intelligence, sensor fusion, situational awareness, edge AI, PyTorch, TensorFlow, C++, Python, Kalman filter, data processing, embedded AI, defense technology, Germany
Requirements
- Degree in Computer Science, Machine Learning, Robotics, Physics or related field
- Proven experience in applied machine learning and sensor data processing
- Strong experience with modern ML frameworks such as PyTorch or TensorFlow
- Solid programming skills in Python and proficiency in C++ for embedded deployment
- Strong understanding of sensor fusion, tracking, and localization concepts
- Comfortable working with imperfect real‑world datasets
- Fluent English (German strongly appreciated)
- Eligibility for German security clearance (German or EU citizenship required)
Responsibilities
- Process and analyze large volumes of real‑world sensor data
- Design, train, and optimize machine learning models for signal classification and noisy data interpretation
- Develop advanced sensor fusion algorithms combining ML techniques with Kalman filters
- Translate ML prototypes into efficient algorithms deployable on embedded systems
- Optimize and quantize ML models for resource‑constrained edge hardware
- Develop predictive models to anticipate environmental changes and entity movements
- Validate and improve algorithms using simulation environments and real‑world field test data
Skills
PythonC++PyTorchTensorFlowKalman filterSensor fusionMachine learningArtificial intelligenceEdge AIData processingEmbedded systems
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