We are looking for a highly skilled Staff Simulation & Software Integration Engineer to drive the development and scaling of our next-generation autonomous driving simulation platform. In this role, you will design and integrate complex simulation pipelines, interface with core ADAS/AD software stacks, and ensure robust system-level validation across SIL (Software-in-the-Loop), HIL (Hardware-in-the-Loop), and cloud environment. You will serve as a key technical leader—bridging simulation, autonomy software, and infrastructure while enabling rapid scenario creation, scalable execution, and automated validation of advanced driver-assistance and autonomous driving features.
Key Responsibilities
- Simulation Platform Development
- Design, develop, and scale a state-of-the-art simulation system for ADAS/AD validation, supporting massive scenario generation, execution, and automated evaluation.
- Develop validation workflows for different parts of the simulation system.
- Implement scenario authoring tools, simulation APIs, and pipelines that integrate seamlessly with autonomy software.
- Develop distributed, cloud-native simulation workflows using Docker, Kubernetes, and CI/CD pipelines.
- Manage simulation data pipelines for large-scale scenario generation, execution, and results aggregation.
- Integration, Verification & Validation
- Interface and integrate the simulation system with AD software stack.
- Build robust adapters and middleware connections across diverse environments.
- Triage and debug integration issues spanning simulation, autonomy stack, and infrastructure layers.
- Ensure simulation stability and robustness on all the platforms.
- Define and implement KPIs, metrics, and validation frameworks for automated evaluation of ADAS/AD features.
- Architecture & Collaboration
- Partner with autonomy engineers, systems engineers, and infrastructure teams to gather requirements, define architectures, and influence system design.
- Mentor junior engineers and set best practices for simulation software integration and infrastructure scaling.
Qualifications (Must-Have)
- Strong software engineering background with expertise in modern C++ and Python.
- Experience with containerization and orchestration (Docker, Kubernetes) for scaling simulation workloads.
- Proven experience building and integrating simulation systems for ADAS/AD or related domains.
- Familiarity with scenario description standards (OpenDRIVE, OpenSCENARIO) and data interchange formats (JSON, YAML).
- Deep understanding of simulation subsystems and core engine components.
- Hands-on experience with middleware and communication frameworks (ROS, DDS, or similar).
- Strong debugging, integration, and triage skills across complex distributed systems.
- Familiarity with automotive simulators like CARLA and CarMaker.
Good to have:
- Knowledge of automotive ECU network architectures, ARXMLs and restbus simulaton on HIL systems (dSPACE, NI).
- Understanding of Vehicle dynamics and subsystems in vehciles.
- Exposure to cloud infrastructures (AWS, GCP, Azure) for distributed simulation execution.
- Experience with data-intensive workflows for large-scale simulation data processing.
- Understanding of real-time systems, multithreading, and optimization for simulation performance.
- Background in sensor simulation/validation (camera, radar, lidar).
- Interest in applying emerging generative AI methods to enhance in-house simulation capabilities.
Education & Experience
- Bachelor’s or Master’s degree in Mechanical Engineering, Computer Science, Robotics, or related field.
- 5+ years of experience in simulation, software integration, or autonomous systems development (5+ years for exceptional candidates with advanced degrees).
At Lucid, we don’t just welcome diversity - we celebrate it! Lucid Motors is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, national or ethnic origin, age, religion, disability, sexual orientation, gender, gender identity and expression, marital status, and any other characteristic protected under applicable State or Federal laws and regulations.
