MITRE ASIA PACIFIC SINGAPORE (MAPS)
Machine Learning Research Engineer
Under the initial sponsorship of the Civil Aviation Authority of Singapore (CAAS), The MITRE Corporation, a U.S.-based, globally renowned research and development company, established its premier air traffic management research center in Singapore in 2015 to support the growth in the Asia Pacific Region. This research center, MITRE Asia Pacific Singapore (MAPS), needs a machine learning research engineer to be part of a dynamic team of multi-disciplinary professionals working to improve air traffic operations in Singapore and the Asia Pacific region. The role offers the opportunity to work on unique aviation datasets and complex operational challenges, collaborate with international experts, and contribute to aviation research with impact across the region.
The ideal candidate has a strong interest in applying machine learning to solve real-world problems in aviation, possesses excellent verbal and written technical communication skills, and strong analytical abilities.
A successful candidate will :
- Implement, train, and evaluate machine learning models under the mentorship of senior researchers and aviation subject-matter experts
- Perform data validation, data preprocessing, and feature engineering
- Conduct literature reviews and adapt deep learning architectures from research papers and emerging literature
- Analyze model performance using both traditional machine learning metrics and operationally relevant metrics
- Support reproducibility, experiment tracking, and model deployment efforts
- Contribute to technical reports and publications, and present findings to operational stakeholders
Required Skills and Experience :
Bachelor's degree in Computer Science, Data Science, Electrical or Computer Engineering, Statistics, Mathematics, Physics, a related technical field, or equivalent experience1–3 years of experience with Python and machine learning libraries (e.g., PyTorch, TensorFlow, scikit-learn)Deep knowledge of machine learning conceptsExperience with GPU-accelerated training of deep learning modelsPreference will be given to candidates who possess any of the following competencies or attributes :
Master’s degree in a related technical fieldExposure to applied research in academic or industrial settingsDemonstrated experience working with real-world or multi-modal data (e.g., time series, geospatial, imagery)Familiarity with deep learning architectures such as CNNs, RNNs, transformers, or autoencodersFoundational knowledge of meteorology or air traffic management conceptsStrong interest in aviationJ-18808-Ljbffr