Staff AI Systems Engineer- Autonomous Driving

What you'll do

• Architect failure-triage and automated root-cause-analysis frameworks for large-scale simulation and vehicle logs.
• Apply AI/ML methods to detect failure modes and integrate automated diagnostics into continuous integration, regression testing, and replay pipelines.
• Set technical direction and engineering practices across teams, partnering with autonomy, validation, and cloud infrastructure groups.

What they ask for

• Master’s degree or Ph.D. in a related technical field, or equivalent practical experience.
• 5+ years of progressive engineering experience in software development, data analytics infrastructure, or automated testing for autonomous vehicles, robotics, or complex distributed systems.
• 2+ years leading technical architecture, engineering strategy, or technical direction across multiple teams.
• Expert proficiency in Python and C++, with experience building production-grade data pipelines, distributed execution frameworks, or testing infrastructure.

Nice to have

• Experience applying LLMs/VLMs, sequence modeling, pattern recognition, or vector embeddings to log classification, failure retrieval, or root-cause analysis.
• Experience with autonomous-driving architectures, simulation/replay testing, or distributed data tools and cloud services.

Pay

$185,000 - $215,000 USD base salary

Tools

Python, C++, ROS/ROS2, MCAP, Protobuf, CAN logs, PySpark, Ray

AI focus

Uses AI/ML, including LLMs/VLMs, anomaly detection, pattern recognition, causal inference, and vector embeddings, for automated failure triage and root-cause analysis.