<h3><span style="font-family: 'times new roman', times, serif;">Who we are</span></h3> <p><span style="font-family: 'times new roman', times, serif;">Gatik, the leader in autonomous middle-mile logistics, is revolutionizing the B2B supply chain with its autonomous transportation-as-a-service (ATaaS) solution and prioritizing safe, consistent deliveries while streamlining freight movement by reducing congestion. The company focuses on short-haul, B2B logistics for Fortune 500 retailers and in 2021 launched the world’s first fully driverless commercial transportation service with Walmart. Gatik's Class 3-7 autonomous trucks are commercially deployed across major markets, including Texas, Arkansas, and Ontario, Canada, driving innovation in freight transportation. </span></p> <p><span style="font-family: 'times new roman', times, serif;">The company's proprietary Level 4 autonomous technology, Gatik Carrier™, is custom-built to transport freight safely and efficiently between pick-up and drop-off locations on the middle mile. With robust capabilities in both highway and urban environments, Gatik Carrier™ serves as an all-encompassing solution that integrates advanced software and hardware powering the fleet, facilitating effortless integration into customers' logistics operations. </span></p> <h3><span style="font-family: 'times new roman', times, serif;">About the role</span></h3> <div> <p><span style="font-family: 'times new roman', times, serif;">Gatik is revolutionizing middle-mile logistics with fully driverless commercial box trucks and tractors operating on fixed B2B routes. As a Senior Systems & Safety Engineer for AI/ML, you will bridge the gap between cutting-edge deep learning algorithms (perception, prediction, planning) and rigorous safety engineering. You will define the functional safety and SOTIF strategies for learned components, establish out-of-distribution (OOD) detection criteria, design runtime AI safety monitors, and construct evidence-backed safety cases for machine learning models running on Level 4 autonomous commercial vehicles.</span></p> <p><span style="font-family: 'times new roman', times, serif;">This role is onsite 5 days a week at our Santa Clara, CA office!</span></p> </div> <h3><span style="font-family: 'times new roman', times, serif;">What you'll do</span></h3> <ul> <li style="font-family: 'times new roman', times, serif;"><span style="font-family: 'times new roman', times, serif;"><strong>SOTIF & ML Safety Architecture:</strong> Lead the implementation of ISO 21448 (SOTIF) and UL 4600 frameworks across Gatik's AI/ML pipelines.</span></li> <li style="font-family: 'times new roman', times, serif;"><span style="font-family: 'times new roman', times, serif;"><strong>Safety Requirements for Learned Systems:</strong> Derive safety requirements and performance boundaries (e.g., false positive/negative limits, edge-case coverage metrics) for neural networks and deep learning models.</span></li> <li style="font-family: 'times new roman', times, serif;"><span style="font-family: 'times new roman', times, serif;"><strong>Runtime Verification & AI Monitors:</strong> Design and validate deterministic AI safety guardrails, out-of-distribution (OOD) detectors, and runtime monitoring mechanisms that fall back to fail-safe actions upon model degradation or uncertainty.</span></li> <li style="font-family: 'times new roman', times, serif;"><span style="font-family: 'times new roman', times, serif;"><strong>Dataset Safety & Bias Assessment:</strong> Establish criteria for training and validation dataset completeness, operational design domain (ODD) coverage, class imbalance, and synthetic vs. real data fidelity.</span></li> <li style="font-family: 'times new roman', times, serif;"><span style="font-family: 'times new roman', times, serif;"><strong>Failure Modes & Effects Analysis:</strong> Conduct systematic HAZOP, STPA, and SOTIF risk analyses specifically targeting deep learning failure modes (e.g., adversarial examples, sensor degradation, lighting/weather edge cases).</span></li> <li style="font-family: 'times new roman', times, serif;"><span style="font-family: 'times new roman', times, serif;"><strong>Safety Case Argumentation:</strong> Author structured safety case arguments (Goulburn/GSN or Goal Structuring Notation) demonstrating acceptable residual risk for AI components in driverless operations.</span></li> </ul> <h3><span style="font-family: 'times new roman', times, serif;">What we're looking for</span></h3> <ul> <li style="font-family: 'times new roman', times, serif;"><span style="font-family: 'times new roman', times, serif;"><strong>Education:</strong> M.S. or Ph.D. in Computer Science, Robotics, Electrical Engineering, Machine Learning, or related field.</span></li> <li style="font-family: 'times new roman', times, serif;"><span style="font-family: 'times new roman', times, serif;"><strong>Experience:</strong> 6+ years in systems/safety engineering or autonomous systems, with at least 3 years explicitly focused on AI/ML safety.</span></li> <li style="font-family: 'times new roman', times, serif;"><span style="font-family: 'times new roman', times, serif;"><strong>Standards Expertise:</strong> Deep working knowledge of ISO 21448 (SOTIF), ISO/PAS 8800, UL 4600, and ISO 26262</span></li> <li style="font-family: 'times new roman', times, serif;"><span style="font-family: 'times