Autonomous Driving Algorithm Engineer

美農機器人·Engineering - Electrical / Electronic / Mechanical

Replied to 4 talents in 7 daysFull Time

HK work visa available

3 to 5 yrs exp

Master

HK $18K-27K/Month

Job Description

Job Responsibilities:

Responsible for the design, development and implementation of core algorithms such as perception, localization, path planning, decision-making, prediction and control for unmanned vehicles and mobile robots.
In-depth research and development of global path planning and local path planning algorithms, covering real-time obstacle avoidance, behavioral decision-making, motion prediction, and speed/acceleration control strategies in dynamic environments.
Optimize and debug path following algorithm, improve tracking accuracy, stability and real-time response ability, and adapt to various chassis dynamics characteristics.
Continuously improve the performance of existing planning and control algorithm modules, including computational efficiency, robustness, generalization ability, and embedded deployment adaptability, and promote modularization and scalability upgrade of software architecture.
Write complete and standardized development documents, technical white papers, interface specifications and test reports to support cross-team collaboration and algorithm productization; participate in algorithm library version maintenance, feature iteration and on-site vehicle/machine debugging and validation.

Requirements:

Master's degree or above, automation, mechanical-electronic, computer science, artificial intelligence, control engineering or related fields; with solid mathematical foundations (linear algebra, probability and statistics, optimization theory) and solid programming skills.
Proficient in C++ (C++11/14) and Python, with experience in embedded system or ROS/ROS2 framework development in a Linux environment, familiar with common algorithm development toolchain (such as CMake, GDB, Git).
Familiar with common perception and planning datasets (such as nuScenes, KITTI, Argoverse), simulation platforms (such as CARLA, LGSVL, Webots) and hardware-in-the-loop (HIL)/vehicle-in-the-loop (VIL) test processes are preferred.
Have good engineering practice awareness and problem-oriented thinking, be able to independently complete the whole process of algorithm module from prototype design, simulation verification, on-vehicle debugging to performance analysis; Have cross-department communication and collaboration ability and technical documentation writing habit.

Software Engineering

C++

OpenCV

English

Mandarin

Cantonese