Robot-Algorithm Engineer-Cluster Scheduling

Hikrobot Co., Ltd.

Location

China

Vacancy for

Human

Employment type

Full-time

Necessary education

Higher

Employer provided salary

0€ per year

Posted at 28.10.2025

Description

Requirements

  1. Master's degree or above, doctoral degree is preferred; computer, mathematics, operations research, automation, industrial engineering, machine learning and other related majors;
  2. Have a solid programming foundation, proficient in C/C++, and at least one tool language (Python, java, etc.);
  3.  Master vehicle path planning Related algorithms, including but not limited to traditional methods based on graph search, and other heuristic intelligent algorithms;
  4. Master graph theory, operations research, optimization algorithms and other theories, including but not limited to linear programming, combinatorial optimization, online optimization, game theory, reinforcement learning, etc.;
  5. Possess strong mathematics Modeling and logical analysis skills, thesis retrieval and reading skills, and good learning skills;
  6. Passionate about solving challenging problems, good communication, collaboration and stress resistance;
  7. The following experience is preferred: Participated in logistics scheduling, capacity scheduling, and intelligent dispatching.Development and debugging of core algorithms for projects such as single and vehicle path planning;

    Check out the full job listings here.

Needed key skills

  • Algorithms
  • Analytical Skills
  • C/C++
  • Coding
  • Problem-solving skills
  • Python
  • Strategic planning
  • Systems Analysis
  • Teamwork
  • Technology savvy
  • Willingness to learn
  • Works well under pressure

Bonuses

Development of intelligent algorithms for cluster dispatching and route coordination for mobile robots. Work at the interface of graph theory, optimization, and machine learning with real-world logistics and automation tasks. The ability to implement advanced techniques (LQR, RL, combinatorial optimization), simulate real-world scenarios, and influence system efficiency in large-scale projects.

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