Staff AI Systems Engineer- Autonomous Driving
Core
Architect and scale intelligent failure triaging and automated Root Cause Analysis (RCA) frameworks for petabyte-scale simulation and real-world vehicle logs to support safe, reliable self-driving vehicles.
Role type
Staff AI Systems Engineer (Autonomous Driving)
Builds
Automated diagnostics toolsets, AI/ML pipelines for failure mode isolation, and integrated testing frameworks for ADAS/AD technologies.
Domain
Autonomous Driving / Robotics / Data Infrastructure
Deliverable
production ML models
Required skills
Python, C++, AI/ML methods (LLMs/VLMs, time-series anomaly detection, causal inference), big data structures, robotics logging formats (ROS/ROS2, MCAP, Protobuf, CAN logs), cloud data storage, distributed execution frameworks, automated testing infrastructure.
Preferred skills
LLMs/VLMs for log classification, autonomous driving software architectures (perception, sensor fusion, localization, motion planning), SiL/HiL/cloud-based replay and simulation testing, distributed frameworks (PySpark, Ray, Databricks/Snowflake, Vector DBs, Apache Airflow, Kubernetes, AWS/GCP).
Responsibilities
Design and implement automated RCA frameworks for petabyte-scale logs; Apply AI/ML methods to isolate failure modes across perception, planning, and control layers; Integrate automated triaging into CI/CD and cloud replay pipelines; Establish best practices for log data structures and ML pipeline reliability; Partner with autonomy software leads and validation engineers to align toolsets.
Seniority
Staff, technical leadership across multiple teams
