Design, develop and improve general operation research solver in linear programming, (mixed) integer programing and general constraint programming.
Design, develop and improve the operational research optimization algorithms based on practical problems, including but not limited to combinatorial optimization, game theory, online optimization, stochastic optimization, linear programming, cybernetics, etc.
Work with industry solution team to support business success.
Salary higher than market average. We are ready to provide the best conditions to the best candidates.
Annual bonus, company options.
Phone expenses compensation.
MS or Ph.D. in operational research, mathematics, computer science, or similar technical field.
Thorough knowledge of scheduling and optimization related concepts, understand one or more of the following algorithms: linear programming, non-linear programming, dynamic programming, combinatorial optimization, meta-heuristic algorithm, evolutionary algorithm, etc.
Deep understanding on classical combinatorial optimization problems and related algorithms, such as bin packing, vehicle routing, and so on.
Practical project experience of using existing commercial or open-sourced optimization solvers, such as CPLEX, Gurobi, LINDO, etc.
5+ years of experience in C/C++ programming.
Excellent written and verbal communication skills in English.
Experience in industry problem solving is a plus.
Experience in distributed/parallel computing is a plus.
Полная занятость, полный рабочий день, у работодателя