COMPANY DESCRIPTION

Singapore Management University is a place where high-level professionalism blends together with a healthy informality. The family-like atmosphere among the SMU community fosters a culture where employees work, plan, organise and play together - building a strong collegiality and morale within the university.

Our commitment to attract and retain talent is ongoing. We offer attractive benefits and welfare, competitive compensation packages, and generous professional development opportunities - all to meet the work-life needs of our staff. No wonder, then, that SMU continues to be given numerous awards and recognition for its human resource excellence.

RESPONSIBILITIES

This position is for School of Computing and Information Systems (SCIS).
Build and maintain end-to-end data pipelines, including data ingestion, cleaning, validation, feature engineering, and dataset versioning.
Develop and manage research codebases for optimization and machine learning experiments, ensuring reproducibility and scalability.
Implement optimization algorithms (e.g., LP/MIP, heuristics, decomposition methods, simulation-based approaches) and integrate them with learning components.
Develop internal tools (e.g., APIs, evaluation frameworks, benchmarking pipelines, dashboards) to support research workflows.
Support large-scale experimentation, including performance optimization, parallelization, and reproducibility.
Collaborate closely with researchers to translate conceptual models into robust, reusable implementations
Other duties as assigned.

QUALIFICATIONS

Bachelor's or Master's degree in Computer Science, Software Engineering, Industrial Engineering, Data Science, Operations Research, or a related field.
Strong programming skills in Python experience with production-quality code (testing, modular design, version control).
Experience building data and/or machine learning pipelines (e.g., pandas, SQL, workflow tools).
Experience implementing algorithms and running large-scale experiments.
Familiarity with Linux environments, Git, and reproducible workflows (e.g., conda, Docker).
Proficiency in using AI tools to support development and experimentation.
Strong problem-solving, communication, and collaboration skills.
Preference for candidate who is familiar with
- Optimization tools (e.g., Gurobi, CPLEX, OR-Tools, Pyomo, cvxpy, JuMP)
- Experience with ML frameworks (e.g., PyTorch, TensorFlow, JAX) and experiment tracking tools (e.g., MLflow, Weights & Biases)
- Experience with cloud or HPC environments and parallel computing frameworks (e.g., Ray, Dask, MPI)
- Experience developing internal research tools (e.g., benchmarking systems, evaluation pipelines, dashboards).

OTHER INFORMATION

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Please note that your application will be sent to and reviewed by the direct employer - Singapore Management University

Research Engineer (1-year contract), SCIS