AI Research Scientist · Internship

What you'll do.

Conduct research on how large language models can support optimization and operations research tasks.
Explore LLM-based methods for mathematical modeling, problem formulation, algorithm design, solver selection, and decision-support workflows.
Develop and test workflows involving coding with LLMs in the loop.
Study how LLMs can generate, debug, verify, and improve optimization models and solver code.
Design evaluation methods and benchmarks for LLM-generated optimization formulations, code, and solutions.
Implement research prototypes and computational experiments.
Analyze failure cases and improve model reliability, correctness, and usefulness.

Candidates pursuing a PhD, Master's degree, or Bachelor's degree in relevant fields are welcomed.
Demonstrated research ability, strong technical depth, and experience in optimization, LLMs, AI agents, algorithms, or machine learning are highly valued.
Ability to work independently in a fast-paced startup environment with evolving priorities.
Excellent communication skills for discussing technical concepts with cross-functional teammates.

Experience with LP, MIP, NLP, or constraint programming.
Ability to translate business problems into mathematical models (variables, objectives, constraints).
Familiarity with solvers like Gurobi, CPLEX, SCIP, or OR-Tools.
Understanding of solver behavior, computational bottlenecks, and model debugging.
Experience with practical problems such as routing, scheduling, or resource allocation.

Expertise in code structure, testing, logging, and building reproducible experiment pipelines.
Ability to integrate AI components with external tools, APIs, and enterprise systems.
Strong judgment on system performance, scalability, and failure handling.
Knowledge of LLM workflows (prompting, retrieval, agents), machine learning evaluation, and structured code generation.