Research Engineer I (Computer Science)

Location: NTU Main Campus, Singapore

Time Type: Full time

Job Description

The Alibaba-NTU Global e-Sustainability CorpLab (ANGEL) represents a key collaboration between Alibaba Group and Nanyang Technological University (NTU). Supported by the Singapore RIE2025 Fund, ANGEL creates and deploys impactful green digital technologies for global sustainability.

ANGEL’s mission aligns seamlessly with Singapore’s national objectives, such as the Singapore Green Plan 2030 and the Singapore Smart Nation Initiative. ANGEL’s work in developing sustainable and equitable digital solutions and promoting a sustainable and green lifestyle will contribute to a smaller carbon footprint. Its holistic approach will help to secure a brighter, more sustainable future for humanity. 

We are looking for a Research Engineer to support innovative research in federated learning and computer vision by designing, developing, and optimizing robust distributed learning frameworks and deep learning models for visual recognition and person re-identification.

Key Responsibilities:

• Design and conduct independent and collaborative research in federated learning and computer vision, including the design and optimization of aggregation, personalization, and clustering strategies for distributed and multi-task learning systems.

• Develop, implement and optimize deep learning models for visual recognition and person re-identification, ensuring robustness and generalization across heterogeneous, non-IID, and decentralized data environments.

• Develop personalized federated learning frameworks, incorporating mutual learning or knowledge distillation techniques to enhance cross-client knowledge transfer while preserving local specialization.

Job Requirements:

• Bachelor’s degree in Computer Science or a related field.

• Demonstrated expertise in federated learning, distributed optimization, and deep learning, with strong understanding of multi-task learning, personalization strategies, and adaptive aggregation mechanisms under non-IID and heterogeneous data settings.

• Hands-on experience in computer vision and representation learning, including unsupervised and camera-aware person re-identification, with the ability to design, implement, and evaluate robust vision models.

• Experience in integrating research prototypes into cloud-based or production-like environments for real-world deployment, scalability evaluation, and system performance optimization is advantageous.

• Good written and oral communication skills

• Competent in ability to work independently / develop solutions under strict timelines / excellent organizational / time management skills

We regret to inform that only shortlisted candidates will be notified.