Consultant (m,w,d) AD-Validation PM - SAE L4 Automated Driving & E2E AI Systems

What you'll doYou lead and structure SAE Level 4 autonomous driving validation programs across the full development lifecycle, from concept phase to series readiness, homologation and operations.You define and operationalize holistic validation strategies for E2E AI‑based AD systems, combining scenario‑based testing, data‑driven validation, simulation, and real‑world testing.You translate regulatory, safety and quality requirements (ASPICE, ISO 26262, SOTIF, homologation, ISO PAS 8800) into executable validation concepts, KPIs and release criteria.You analyze the validation implications of key AD system components, including camera, radar, lidar, sensor fusion, localization, prediction, planning, control, data pipelines and runtime monitoring.You analyze and orchestrate SiL, HiL, MiL and vehicle‑level testing and ensure seamless integration into automated CI/CD pipelines.You drive scalable validation approaches for AI models (including coverage metrics, corner‑case detection, data curation strategies, and confidence arguments).You define AI model validation KPIs and acceptance thresholds, including scenario coverage, ODD coverage, perception and planning performance, uncertainty calibration, robustness, latency, temporal consistency, rare-event behavior and regression stability.You align validation scope and evidence with Type Approval and AD Safety Management Systems (AD‑SMS).You act as central interface between AI development teams, system engineers, toolchain providers, test organizations, and external stakeholders (e.g. authorities, partners, suppliers).You manage stakeholders at program and management level, including reporting, risk management, decision preparation and escalation.You proactively identify validation risks related to AI behavior, operational design domain (ODD) boundaries, and system interactions.Who you areYou hold a university degree in Engineering, Computer Science, Artificial Intelligence, or a related field.You demonstrate a solid understanding of AI/ML concepts for autonomous driving, including E2E vision-heavy approaches, data‑driven development, and AI‑specific validation challenges.You possess a deep understanding of the validation challenges of SAE Level 4 automated driving systems, including ODD definition, scenario coverage, residual risk assessment, safety case development, and evidence-based release decisions.You have hands-on experience with simulations, SiL, and HiL testing, ideally integrated into automated CI/CD environments.You bring a strong technical understanding of AD system architectures, including modular pipelines, E2E AI models, and hybrid architectures, as well as their impact on validation strategy and safety argumentation.You have practical knowledge of camera, radar, and lidar sensor characteristics, sensor fusion principles, calibration, synchronization, degradation effects, and typical failure modes relevant for AD validation.You have a proven track record in high-reliability industries (automotive, aerospace, medical), with deep exposure to ASPICE, ISO 26262, SOTIF, and homologation processes.You demonstrate strong analytical and structuring skills to translate abstract safety, regulatory, and AI risks into concrete validation strategies.You are able to work proactively and independently in agile, cross-functional teams, lead validation initiatives, and align multiple internal and external stakeholders.Good to knowFull ownership and entrepreneurial freedom A high-impact role in a dynamic, international setup The opportunity to actively shape AI-driven business growth Direct exposure to top management and international stakeholders Competitive compensation with performance-based incentives