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 Car. Maker, or VTD) and scenario standards (Open. SCENARIO, Open. DRIVE). 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 d. SPACE, NI, or Vector hardware, including ARXM - Ls 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 ROS 2, 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.