Research Engineer

2 days ago

Singapore Singapore-MIT Alliance for Research and Technology Centre Full time

Project Overview This role contributes to Towards Self-Evolving LLM Systems for Optimization Problem Formulation under M3S. We build LLMs that evolve both optimization correctness and efficiency by curating an experience library, applying classic OR techniques (e.g., branch-and-cut, column/row generation) and systematically matching the right method to the right problem structure, and supporting human–AI collaboration for large-scale OR problems and real-world tasks (smart cities, transportation, resource allocation). Key Responsibilities Conduct research and develop systems-level prototypes that focus on self-evolving LLM systems for OR, including experience library curation, probabilistic reasoning, solver-confidence integration, and efficiency-aware formulation. Publish research results in top-tier conferences and journals, with focus on venues associated with OR, AI and transportation science. Collaborate with OR experts and local partners in Singapore to address applied operations scenarios and pilot implementations. Assist in grant writing, project management, and other administrative duties related to research activities. Requirements Minimum Bachelor's Degreein Computer Science, Operations Research, Data Science, Transportation Engineering, or related fields. Hands-on with LLM agent systems, training/fine-tuning and data science workflows (data preparation/ETL, feature engineering, experiment design and metrics). Strong background in OR formulations (e.g., integer programming, submodular optimization) and integration with OR solvers (e.g., Gurobi/CPLEX) are essential. Project-level experience with building datasets/benchmarks and efficiency evaluation is highly desired. Strong publication record in top-tier AI/ML/OR conferences and journals. DESIRABLE: Experience leading human-in-the-loop, systems-level studies using Singapore data and piloting with industrial sector, from dataset/benchmark design to field validation. Excellent written/oral communication and cross-functional collaboration skills. To apply, please visit our website at: Interested applicants are invited to send in their full CV/resume, cover letter and list of three references (to include reference names and contact information). We regret that only shortlisted candidates will be notified #J-18808-Ljbffr

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