LinfinityGNSS
Artificial Intelligence Senior Engineer with GNSS knowledge
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Job Description
We are seeking an AI/ML Engineer with a strong interest in GNSS and space applications to join our team and help drive innovation in satellite navigation technology. In this role, you will apply machine learning and artificial intelligence techniques to solve complex challenges in GNSS signal processing, positioning accuracy, and system optimization. Success in this position means bringing modern data-driven approaches to a traditionally deterministic engineering field, helping to build smarter, more adaptive, and more resilient navigation systems. This role sits at the intersection of applied AI and space engineering, contributing directly to the organization's next generation of GNSS technologies.
Responsibilities
- Design, develop, and train machine learning models to improve GNSS signal accuracy, interference detection, and error correction
- Apply AI/ML techniques (e.g., deep learning, anomaly detection, sensor fusion) to enhance positioning, navigation, and timing (PNT) performance
- Analyze large-scale GNSS datasets to identify patterns and extract features for model development
- Collaborate with GNSS engineers, software teams, and space systems specialists to integrate AI models into navigation pipelines
- Prototype and validate novel AI-driven approaches to GNSS challenges such as multipath mitigation, jamming/spoofing detection, and signal robustness
- Contribute to technical documentation, research publications, and patent filings related to AI-enabled GNSS innovations
- Stay current with advancements in AI/ML methods and their emerging applications within the space and satellite navigation sector
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Qualifications
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- Degree in Computer Science, Data Science, Electrical Engineering, Aerospace Engineering, or a related field (advanced degree preferred)
- Strong hands-on experience with machine learning and deep learning techniques, including model development, training, and evaluation
- Proficiency in relevant programming languages and frameworks (e.g., Python, TensorFlow, PyTorch, scikit-learn)
- Familiarity with GNSS systems, signal processing, or satellite navigation concepts
- Strong analytical and problem-solving skills, with a genuine curiosity about applying AI to real-world engineering problems
- Excellent verbal and written communication skills
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