Machine Learning Research Engineer
4 days ago
**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.
- 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 effortsContribute 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 experience
- 1-3 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 models
- Master’s degree in a related technical field
- Exposure to applied research in academic or industrial settings
- Demonstrated 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 autoencoders
- Foundational knowledge of meteorology or air traffic management concepts
- Strong interest in aviation
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