Salary: strong>30-60K
Experience requirements: strong>Unlimited experience
Educational requirements: PhD or above
Job Description: strong>
Direction 1:
1. Responsible for the design and implementation of optimization and scheduling algorithms for artificial intelligence services, as well as industry related technical analysis
2. Responsible for optimizing and scheduling algorithms for artificial intelligence service systems, driving iterative product development; Resolve various issues encountered during the implementation of scheduling optimization algorithms
Direction 2:
1. Participate in or be responsible for the overall architecture design, functional module design, key technology breakthroughs and innovations of AI4Solver, continuously improve and optimize the technical architecture and algorithms of the system, and build competitive AI4Solver solutions and technologies
2. Participate in or be responsible for gaining insights into the progress and trends of AI4Solver in the industry, continuously exploring the commercial value points of AI enabled operational optimization and numerical computing engines, and falling into the iteration of AI4Solver requirements to enhance product competitiveness
3. Participate in research on machine learning and reinforcement learning based solvers, continuously improve and optimize algorithms for important operations research and numerical computation problems in the AI4Solver field, and provide solutions based on the integration of AI and solvers, including:
(1) Research on the abstraction, representation, and solver strategy learning of mathematical programming problems using learning methods
(2) Efficient generation of mathematical programming models based on natural language processing technology
(3) Building an AI solver framework and evaluating system acceleration for solver learning optimization, such as black box optimization methods
(4) Develop competitive technical solutions based on the combination of AI and traditional numerical computing for AI assisted simulation
Direction One:
1. PhD in Operations Research, Applied Mathematics, and Computer Science
2. Master the algorithm principles of optimization and scheduling, and be proficient in mathematical modeling based on business problems. Fully understand the role, applicable conditions, and shortcomings of algorithms in practical applications, have project or research experience in solving application problems, and be good at communication and expression
3. Proficient in one or more programming languages of C++/Java/Python, familiar with relevant optimization software or simulation tools, such as Cplex, Gurobi, Lindo, and others
4. Familiar with algorithms and concepts related to optimization and scheduling, familiar with one or more of the following algorithms: linear programming, nonlinear programming, dynamic programming, combinatorial optimization, metaheuristic algorithms, evolutionary algorithms, etc
5. Have good analytical and problem-solving skills, enjoy learning, and be good at thinking
6. Those who have personally implemented complex optimization and scheduling algorithms are preferred; Experience in optimization and scheduling related projects is preferred
Direction 2:
1. Master the algorithm principles of decision optimization and numerical computation (such as operations research optimization, numerical simulation, machine learning, and data mining), and be proficient in modeling and solving business problems. Fully understand the role, applicable conditions, and shortcomings of algorithms in practical applications, have project or research experience in solving application problems, and be good at communication and expression
2. Familiar with commonly used operations research optimization/numerical computation algorithms, reinforcement learning algorithms, machine learning algorithms, big data platforms, optimization software (cplex, gurobi), numerical simulation platforms, and related machine learning and big data development tools (such as MXNet, TensorFlow, Spark, Hive, etc.), experience in distributed system development is preferred
3. Good communication and teamwork skills, as well as excellent analytical and problem-solving abilities, willing to learn and good at thinking
4. Experience in implementing AI algorithms based on Ascend chips is preferred
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Deadline: December 16, 2025
Please send your CV or resume as an attachment to the following email address:
mailto: rbhr@hrcenter.co.uk
With the subject line formatted as: 'Name + Position + Company Name + Location'.