implement algorithmic solutions for optimization and constraint satisfaction problems (NDA project – we will tell you more at the interview);
formulation and programming of optimisation problems for different domains (logistics, finance, farma, etc.);
support classical dev in quantum algorithms ;
clearly documenting and communicating the work and progress to the internal development teams.
knowledge in C++ is a plus;
basic knowledge of CUDA;
experience in parallel programming using CPUs and/or GPUs, understanding the basics of parallel computing: MPI, OpenMP, multithreading technologies;
experience with the git version control system.
good knowledge in Python programming language: numpy, scipy; basic machine-learning frameworks: PyTorch, TensorFlow, or equivalent;
knowledge of the basic properties and methods of solving basic types of mathematical programming problems (Linear Programming, Mixed Integer Linear Programming, Quadratic Programming, Constrained Programming);
good knowledge in numerical linear algebra: matrix decompositions, linear systems solution;
knowledge of the basic solvers for industrial optimization problems;