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Gatik

Robot type
Autonomous Vehicle
Location
Santa ClaraCaliforniaUSA
Job type
Artificial Intelligence
Posted
Sep 2, 2026
Salary
$160,000–$220,000 a year
Full-time

Senior Systems & Safety Engineer – AI/ML

Job description

We have delivered complete, proprietary AV technology - an integration of software and hardware - to enable earlier successes for our clients in constrained Level 4 autonomy. By choosing the middle mile – with defined point-to-point delivery, we have simplified some of the more complex AV challenges, enabling us to achieve full autonomy ahead of competitors. Given extensive knowledge of Gatik’s well-defined, fixed route ODDs and hybrid architecture, we are able to hyper-optimize our models with exponentially less data, establish gate-keeping mechanisms to maintain explainability, and ensure continued safety of the system for unmanned operations.

Visit us at Gatik for more company…

Job responsibilities

  • SOTIF & ML Safety Architecture: Lead the implementation of ISO 21448 (SOTIF) and UL 4600 frameworks across Gatik's AI/ML pipelines.
  • Safety Requirements for Learned Systems: Derive safety requirements and performance boundaries (e.g., false positive/negative limits, edge-case coverage metrics) for neural networks and deep learning models.
  • Runtime Verification & AI Monitors: 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…
  • Dataset Safety & Bias Assessment: Establish criteria for training and validation dataset completeness, operational design domain (ODD) coverage, class imbalance, and synthetic vs. real data fidelity.
  • Failure Modes & Effects Analysis: Conduct systematic HAZOP, STPA, and SOTIF risk analyses specifically targeting deep learning failure modes (e.g., adversarial examples, sensor degradation, lighting/weather edge cases).
  • Safety Case Argumentation: Author structured safety case arguments (Goulburn/GSN or Goal Structuring Notation) demonstrating acceptable residual risk for AI components in driverless operations.

Job requirements

  • Education: M.S. or Ph.D. in Computer Science, Robotics, Electrical Engineering, Machine Learning, or related field.
  • Experience: 6+ years in systems/safety engineering or autonomous systems, with at least 3 years explicitly focused on AI/ML safety.
  • Standards Expertise: Deep working knowledge of ISO 21448 (SOTIF), ISO/PAS 8800, UL 4600, and ISO 26262
  • Technical Skills:
  • AV Domain Knowledge: Strong understanding of sensor modalities (LiDAR, Radar, Cameras, IMUs) and their failure modes in adverse weather/environmental conditions.
  • Track record of taking a machine-learning-based L4 autonomous vehicle system to driverless commercial deployment.
  • Direct experience with data generation/curation tools, active learning, and automated edge-case extraction pipelines.
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