Nullmax

Experience Requirements:

• Experience in trajectory prediction-related algorithms (such as Graph Neural Network, Transformer, Deep Reinforcement Learning, etc.) is preferred.

Other Requirements:

• Possess good programming skills, proficient in C++/Python, and familiar with the Linux development environment.

• Have good ability to read and understand English literature, strong learning ability and a strong desire for knowledge.

• Have good sense of teamwork, communication skills, coordination ability and summary ability.

• Able to work under pressure.

Responsibilities:

• Design, develop, debug and conduct real-vehicle verification of autonomous driving prediction or planning algorithms based on learning methods.

• Design evaluation schemes and conduct tests for prediction or planning algorithms.

• Work closely with the perception module to complete the development and debugging of the system.

Education Requirements:

• Major in computer science, automation, mathematics, automotive engineering or other related fields.

Experience Requirements:

• Experience in optimal matching of lanes, traffic lights, etc.

• Experience with multi-frame smoothing and optimization algorithms for reference lines.

• Knowledge background in NN models for local map road topology generation such as MapTr is a plus.

Other Requirements:

• Foundation in computational graphics and 3D set element processing.

• Familiar with optimal road network matching algorithms (KM, VF2, PDA).

• Proficient in C++.

• Familiar with various optimization algorithms and algorithm libraries (Eigen, OSQP).

• Able to model and reason about complex environments.

Responsibilities:

• Generate and track reference lines and lane topologies based on lane line perception, semantic maps, and traffic flow clustering.

• Understand and infer the regulatory boundaries of the road environment and realize drivable area reasoning.

• Design and develop a matching and fusion framework based on real-time perception and prior semantic maps.

• Identify occluded areas and calculate risk speed limits.

• Perform fusion matching and recognition of lane types, and matching between traffic lights and lanes.

Experience Requirements:

• Experience in vehicle-side mapping, online map post-processing, or crowdsourced mapping is preferred.

• Familiarity with automotive sensors (cameras, radar, GNSS, IMU, wheel speed sensors).

Other Requirements:

• Familiar with semantic SLAM frameworks, online mapping algorithms, and backend optimization.

• Knowledge of ICP, particle filtering, nonlinear optimization, Kalman filters, or multi-sensor fusion.

• Proficient in C++.

• Scripting skills for rapid prototyping.

• Strong problem-solving, communication, and teamwork skills.

Responsibilities:

• Track and maintain geometric and semantic information for local static objects in mass-production projects.

• Ensure absolute and relative accuracy of maps under diverse driving conditions.

• Design, implement, and maintain vehicle-side memory mapping algorithms.

• Achieve semantic localization using prior maps.