Pursue cutting-edge careers at the intersection of functional safety and artificial intelligence with Safety Engineer Expert – Machine Learning - ISO 26262 jobs. This highly specialized profession is dedicated to ensuring the safe development, integration, and deployment of machine learning (ML) and AI-based components within safety-critical automotive systems, primarily governed by the ISO 26262 standard. Professionals in this role act as the crucial bridge between data scientists, software engineers, and traditional safety teams, translating complex ML behaviors into quantifiable safety arguments. Typically, a Safety Engineer Expert for Machine Learning is responsible for defining and implementing the overall safety strategy for ML-enabled systems. This involves creating safety concepts, performing hazard analysis and risk assessment (HARA) specific to AI uncertainties, and defining safety goals. A core part of the role is establishing and validating the safety lifecycle processes for data-driven development, including data management, model training, testing, and monitoring. Experts are tasked with selecting appropriate techniques for achieving and verifying safety targets, such as redundancy, diverse ML models, runtime monitoring, and out-of-distribution detection. They also lead the generation of critical safety documentation required for compliance and certification. To excel in these jobs, individuals must possess a rare blend of deep competencies. A strong foundation in ISO 26262, its part 11 (guideline on application to semiconductors), and emerging standards like SOTIF (ISO 21448) is essential. Equally important is a robust understanding of machine learning fundamentals, including neural network architectures, training methodologies, and their inherent limitations (e.g., bias, overfitting, interpretability). Technical skills often include proficiency in programming (Python, C++), simulation tools, and requirements management systems. Key soft skills include analytical problem-solving, cross-functional leadership to guide multidisciplinary teams, and meticulous attention to detail for documentation and verification evidence. Common requirements for these positions include an advanced degree in computer science, electrical engineering, robotics, or a related field, coupled with several years of hands-on experience in both functional safety and applied machine learning. Candidates are expected to demonstrate a proven track record of contributing to safety-critical product development cycles. For engineers passionate about shaping the future of autonomous and intelligent vehicles, Safety Engineer Expert – Machine Learning - ISO 26262 jobs represent a premier and impactful career path, offering the challenge of solving some of the industry's most complex safety puzzles.
