Senior Simulation Algorithm Developer

该职位来源于猎聘 Role Mission Develop high-fidelity, scalable, and measurable simulation capabilities for training and validating end-to-end driving models, planning algorithms, and active safety functions. Enable reproducible open-loop and closed-loop evaluation across large scenario sets before vehicle deployment.

Key Responsibilities

• Develop simulation algorithms and components for scenario replay, closed-loop traffic interaction, vehicle dynamics, and driving-agent behavior.
• Build methods to convert real-world driving logs and scenario definitions into executable and measurable simulation cases.
• Develop scenario-generation, variation, and coverage-expansion methods for rare events, safety-critical interactions, and long-tail driving conditions.
• Integrate simulation with planning, end-to-end models, active safety software, and evaluation pipelines.
• Define and implement metrics for scenario realism, behavioral plausibility, simulation stability, coverage, and test reproducibility.
• Improve simulation runtime performance, parallel execution, determinism, and resource efficiency for large-scale regression campaigns.
• Analyze discrepancies between simulation, replay, HIL, and real-vehicle results, and drive targeted fidelity improvements.
• Work with data and platform engineers to integrate simulation workloads into automated training, evaluation, and CI/CD workflows.

  Required

  Qualifications

• Bachelor’s degree or above in Computer Science, Robotics, Control Engineering, Applied Mathematics, or a related discipline.
• 5+ years of experience in simulation, autonomous driving, robotics, game engines, or related algorithmic software development.
• Strong programming skills in Python and C++.
• Solid understanding of vehicle dynamics, agent modeling, numerical simulation, or closed-loop decision-making systems.
• Experience developing scenario-based or closed-loop simulation rather than only operating third-party simulation tools.
• Experience debugging complex algorithmic systems and evaluating simulation results quantitatively.
• Familiarity with Linux, Git, automated testing, and production development workflows.

  Preferred

  Qualifications

• Experience with one or more AD simulation platforms, such as CARLA, CarMaker, VTD, or proprietary simulation systems.
• Experience with SIL/HIL integration and large-scale automated regression.
• Experience with generative scenario modeling, neural reconstruction, neural rendering, world models, or learned traffic agents.
• Knowledge of active safety and planning evaluation metrics.

  Experience optimizing distributed or GPU-accelerated simulation workloads.