We are seeking a Senior Simulation & Software Integration Engineer to take full ownership of our next-generation autonomous driving simulation platform. This is not a "pure software" role; we need a hybrid engineer who understands the physics and complexities of automotive systems as deeply as the code that simulates them.
You will be the bridge between abstract autonomy algorithms and real-world vehicle behavior. You won’t just follow a spec—you will define the requirements, think creatively to solve bottleneck issues in SIL/HIL, and implement the "next-gen" workflows that allow Lucid to validate ADAS features at a global scale. If you are a problem-solver who enjoys getting your hands dirty in both C++ and vehicle dynamics, this is your role.
Key Responsibilities
- End-to-End Ownership: Drive the design and implementation of simulation pipelines. You will take high-level ADAS requirements and turn them into functional, scalable simulation scenarios.
- Hybrid Integration: Build and maintain the "glue" between our autonomy software stack and simulation engines. You will ensure that the software behaves identically whether it’s in a cloud-native SIL environment or a bench-top HIL rack.
- Creative Problem Solving: Identify gaps in current simulation capabilities (e.g., sensor fidelity, edge-case generation) and implement "out-of-the-box" solutions using modern tools like CARLA, Unreal Engine, or generative AI.
- Validation Frameworks: Define and implement the KPIs and automated metrics that determine if a new software build is "safe" for the road.
- Technical Mentorship: Act as a senior lead within the simulation team, triaging complex integration bugs that span across software, hardware, and infrastructure layers.
Qualifications (The "Must-Haves")
- The Hybrid Mindset: Strong software engineering fundamentals (Modern C++, Python) combined with a solid grasp of how a vehicle actually moves and thinks.
- Ownership Pedigree: Proven track record of taking a simulation project from "concept" to "production validation."
- Simulation Power User: Professional experience with automotive simulators (CARLA, IPG CarMaker, or VTD) and scenario standards (OpenSCENARIO, OpenDRIVE).
- Infrastructure Fluency: Comfortable with Docker and CI/CD pipelines. You should know how to containerize a simulator to run 10,000 tests in the cloud.
- Systems Debugger: Exceptional ability to triage issues where the root cause could be anything from a race condition in the code to a misconfigured vehicle plant model.
Great to Have (The "Differentiators")
- HIL Expertise: Experience with dSPACE, NI, or Vector hardware, including ARXMLs and rest-bus simulation.
- Physics & Sensors: Deep understanding of vehicle dynamics (multi-body) or the physics of Lidar/Radar/Camera sensor modeling.
- Next-Gen Tech: Experience applying Generative AI or Neural Simulation to create realistic driving environments.
- Middleware Mastery: Deep knowledge of ROS2, DDS, or custom high-performance IPCs.
Education & Experience
- Bachelor’s or Master’s degree in Mechanical Engineering, Robotics, Computer Science, or a related field. We value the "Automotive + SW" crossover highly.
- 5+ years of professional experience in ADAS/AD simulation or software integration.
