Functional Safety AI Engineer, Tesla AI

The AI Platform Integration team is seeking a Functional Safety Engineer to design and develop cutting-edge safety-critical systems for seamless integration of AI-driven technologies into AI platforms. We are looking for experienced candidates passionate about ensuring safety and reliability in innovative AI applications. The AI Platform Integration team focuses on embedding AI solutions into safety-critical vehicle functions, such as autonomous driving, predictive control systems, and real-time decision-making. You will help design and build software and integration frameworks that meet stringent safety and reliability standards. Your role will involve determining optimal system design paradigms, communication protocols, and monitoring strategies while collaborating with a team of functional safety engineers, software developers and hardware engineers to establish robust processes, tools, and frameworks that set or exceed industry benchmarks. This is a high-visibility role with significant responsibility. You will work cross-functionally with AI development, hardware, and systems engineering teams to achieve integration goals and meet safety requirements you help define. Additionally, you will contribute directly to software solutions across the full vertical stack to address these requirements. Join a diverse team of experts across multiple domains to pioneer industry-first integrations of AI into vehicle safety systems.

Responsibilities

Partner with cross-functional engineering teams to define integration strategies, evaluate architectural trade-offs, and ensure AI platform designs meet functional safety objectives across compute, sensing, and actuation layers Lead functional safety activities such as Hazard Analysis and Risk Assessments (HARAs), Design Failure Mode and Effects Analysis (DFMEAs), and Safety Requirements definition using internal and industry-standard tools to ensure high system reliability and performance Leverage simulation, SIL/HIL testing, and fleet data to validate safety assumptions and monitor real-world performance of AI-driven systems Implement safety-critical software as needed to meet requirements in system architecture, with a focus on monitoring, fault detection for AI platforms Ensure follow-through on design and integration aspects across various teams, establishing milestones from concept to deployment (e.g., simulation testing, engineering validation, and production readiness) Shape the safety concept validation plan to ensure high-quality test cases for AI systems, both in-vehicle and in simulation environments

Requirements

Experience designing safety-critical systems, preferably in AI or autonomous systems contexts First-hand experience with automotive safety standards (such as ISO 26262) and relevant tools, including Hazard and Risk Assessment (HARA) and/or Failure Mode and Effects Analysis (FMEA) and/or Fault Tree Analysis Deep technical expertise in any of the following: AI system integration, embedded systems, real-time software development, or vehicle control systems Experience with testing and validating safety-critical software, particularly in AI or machine learning applications to support robust Safety Cases Experience of designing systems with stringent availability and safety requirements Proficiency in software development leveraging agentic workflows is preferred (e.g., machine learning frameworks or real-time processing) Experience in C++, Python, or similar programming is preferred