Staff AI Systems Engineer- Autonomous Driving

In this role, you will operate as a Staff AI Systems Engineer, setting technical direction across multiple teams, influencing architecture and engineering standards, and elevating technical capabilities across the organization.
We are seeking a Systems Engineer with strong leadership skills to build and enhance our AI-focused systems engineering and testing frameworks. In this role, you will guide the design, implementation, and evaluation of our Advanced Driver Assistance Systems (ADAS) and Autonomous Driving (AD) technologies. You will serve as the technical lead for a cross-functional team, integrating modern software development practices to help realize safe, reliable self-driving vehicles and empower our global R&D teams.
Responsibilities:
Architect and scale intelligent failure triaging and automated Root Cause Analysis (RCA) frameworks capable of processing petabyte-scale simulation and real-world vehicle logs.
Apply modern AI/ML methods (e.g., LLMs/VLMs, time-series anomaly detection, statistical pattern recognition, and causal inference) to automatically isolate failure modes across perception, planning, control, and vehicle platform layers.
Integrate automated triaging into continuous integration, regression testing, and cloud replay pipelines (SiL/HiL/ViL) to streamline software release cycles and raise validation standards across engineering groups.
Establish best practices for log data structures, automated analytics workflows, vector search/embeddings for failure mode retrieval, and ML pipeline reliability.
Partner directly with autonomy software leads, validation engineers, and cloud infrastructure teams to align toolsets and integrate automated diagnostics into day-to-day R&D workflows.
Master’s degree or Ph.D. in Computer Science, Computer Engineering, Robotics, Electrical Engineering, or 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 of experience leading technical architecture, setting engineering strategy, or guiding technical direction across multiple engineering teams.
Expert proficiency in Python and C++, with demonstrated experience building production-grade data pipelines, distributed execution frameworks, or testing infrastructure.
Hands-on experience working with big data structures, robotics logging formats (e.g., ROS/ROS2, MCAP, Protobuf, CAN logs), and cloud data storage.
Preferred Qualifications:
Demonstrated experience applying LLMs/VLMs, sequence modeling, pattern recognition, or vector embeddings to log classification, failure mode retrieval, or automated root cause analysis.
In-depth understanding of autonomous driving software architectures (perception, sensor fusion, localization, motion planning, vehicle control).
Experience operating within SiL, HiL, or cloud-based replay and simulation testing setups at scale.
Experience with distributed frameworks and data tools such as PySpark, Ray, Databricks/Snowflake, Vector DBs, Apache Airflow, Kubernetes, and AWS/GCP services.

Employment type
Full-time

Work arrangement
Hybrid