Director, Simulation and Evaluation - Autonomous Driving

As the Director for Simulation and Evaluation, you will sit at the center of the Global AI Backbone, architecting the multi-level simulation ecosystems required to train, evaluate and validate next-generation Foundation Models. You will bridge the gap between high-fidelity sensor simulation and generative world models, ensuring our AI systems are statistically proven to be safe and robust before hitting the road.
This is a global role that requires you to define and manage a global simulation and evaluation ecosystem that enables continuous development and deployment of our ADAS systems.
Key Responsibilities:
Lead AI Simulation & Foundation Model Strategy: Define the roadmap for high throughput, closed-loop simulation.
Research and propose new methodologies to assess the quality, safety, and realism of ML models used for training, evaluation and validation of L2++ and L4 automated driving stacks.
Architect Evaluation Frameworks: Build the infrastructure. Develop tools that allow for rapid iteration of Foundation Models, ensuring model improvements translate into measurable gains in fleet-wide performance.
Drive Generative AI Innovation: Lead the development of World Models to predict and generate complex, realisticedge cases. Build data pipelines for signal discovery, data labeling, and metric computation based on large-scale simulations.
Production Release Authority: Establish the "gold standard" for evaluation that informs SoP (Start of Production) and model release decisions. Translate complex simulation data into technical strategy documentation for executive decision-making.
Global Technical Leadership: Lead, mentor and inspire a cross-functional global team of SWEs, Data Scientists, and ML experts, fostering a culture of rigorous statistical validation and innovative engineering.
Basic Qualifications:
Master’s or PhD in Computer Science, Electrical Engineering, Machine Learning, Statistics, Physics, or a related quantitative field.
10+ years of experience in software engineering, with a specific focus on embedded systems, automotive, or robotics.
7+ years of experience leading complex software projects from concept to production within the ADAS or Autonomous Driving domain.
Direct, hands-on experience with L2++ or L4 system Start of Production (SoP), specifically overseeing simulation, testing, and validation protocols for high-stakes deployments.
5+ years of involvement with the development or evaluation of large-scale AI, LLMs, or World Models/Generative AI models for simulation and behavioral prediction.
Expert-level understanding of multi-level simulation platforms, including high-fidelity sensorlevel simulation for perception and scalable object-level simulation for behavioral training.
Proven mastery of data-driven report writing and technical strategy documentation designed for executive decision-making and safety case justifications.
Preferred Qualifications:
5+ years of experience with high-throughput simulation, GPU-accelerated technologies (CUDA), parallel computing, and Reinforcement Learning (RL).
Mastery of C++ and Python. Experience building automated data pipelines for signal discovery, data labeling, and large-scale metric computation.
5+ years of experience managing and mentoring global, multi-disciplinary teams of Software Engineers, Data Scientists, and ML experts.
Working knowledge of automotive industry safety standards and regulations (e.g., ISO 26262, SOTIF) as they apply to virtual validation.

Employment type
Full-time

Work arrangement
Hybrid