SIL/WorldSim Simulation Engineer

Job Description

• You will lead or play a key role in building our in-house simulation engine and platform, using it to tackle some of the most exciting frontier challenges in autonomous driving. This role goes beyond "using tools", cause you will help define how future systems are validated. Your work will directly impact algorithm iteration speed and system safety boundaries.
• Build High-Fidelity Virtual Worlds: Design and implement next-generation simulation engines with a strong focus on ultra-realistic sensor simulation, vehicle dynamics, and traffic flow modeling to reproduce highly complex real-world scenarios.
• Design Scalable Data & Workflow Systems: Architect and optimize high-throughput, low-latency data pipelines to efficiently schedule and execute large-scale simulation workloads. Develop algorithm-driven workflows such as procedural scenario generation and semantic-to-scene automatic construction to dramatically improve scenario diversity and efficiency.
• Enable Core Business Validation Loops: Deeply participate in the construction of various business processes based on simulators, clarify the capability boundaries of autonomous driving algorithms through simulation, and provide deterministic guidance for R&D. Explore deep integration between simulation and teleoperation systems, enabling ultra-realistic sandbox environments for remote intervention and training.
• Enhance Tooling & Developer Experience: Continuously improve scene editing, testing, and analysis toolchains, allowing algorithm engineers to focus on core model development rather than simulation complexity.

Requirements

• Core Qualifications: Bachelor's degree or above in Computer Science, Vehicle Engineering, Automation, or related fields. Strong programming skills in C++ and Python, with a passion for deep technical problem-solving (You will join a group of engineers who Aim for the Highest).
• System & Simulation Expertise: Proficient in Linux development environments with solid system architecture and design capabilities. Hands-on experience using or developing simulation systems (e.g. CARLA, AirSim, VTD), with deep understanding of timing, synchronization, and performance optimization.
• Modeling & Engine Knowledge: Strong background in physical simulation, sensor modeling, and vehicle dynamics. Experience in computer graphics or game engines (Unreal Engine / Unity) is a significant plus.
• Problem Solving & Collaboration: Excellent analytical and problem-solving skills, strong ownership mindset, and solid cross-team communication abilities.
• Preferred Qualifications:
  • Experience in autonomous driving simulation development and integration.
  • Familiarity and have practical application experience with OpenX standards (OpenSCENARIO / OpenDRIVE).
  • Experience deploying and managing large-scale simulation workloads using cloud-native technologies (Docker, K8s).
  • Knowledge of machine learning or deep learning, especially data-driven or reinforcement learning applications in simulation.