Lead AI Systems Engineer – Autonomous Driving

About the role

As Lead AI Systems Engineer you will set technical direction across multiple teams, influence architecture and engineering standards, and raise the technical capabilities of the organization. You will guide the design, implementation, and evaluation of ADAS and autonomous driving technologies, integrating modern software development practices to deliver safe, reliable self‑driving vehicles.

Key responsibilities

• Architect and scale intelligent failure‑triaging and automated root‑cause analysis frameworks that process petabyte‑scale simulation and real‑world vehicle logs.
• Apply modern AI/ML methods (LLMs/VLMs, time‑series anomaly detection, statistical pattern recognition, causal inference) to isolate failure modes across perception, planning, control, and vehicle platform layers.
• Integrate automated triaging into CI, regression testing, and cloud replay pipelines (SiL/HiL/ViL) to streamline release cycles and raise validation standards.
• Establish best practices for log data structures, automated analytics workflows, vector search/embeddings, and ML‑pipeline reliability.
• Partner with autonomy software leads, validation engineers, and cloud infrastructure teams to embed diagnostics into daily R&D workflows.

Required profile

• Master’s degree or Ph.D. in Computer Science, Robotics, Electrical Engineering or related 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, setting engineering strategy, or guiding direction across multiple engineering teams.

Required skills

• Expert proficiency in Python and C++.
• Experience building production‑grade data pipelines, distributed execution frameworks, or testing infrastructure.
• Hands‑on work with big‑data structures and robotics logging formats (ROS/ROS2, MCAP, Protobuf, CAN logs).
• Familiarity with AI/ML techniques such as LLMs, VLMs, sequence modeling, pattern recognition, vector embeddings.
• Knowledge of autonomous driving software stacks (perception, sensor fusion, localization, motion planning, vehicle control).
• Experience with distributed frameworks and tools: PySpark, Ray, Databricks/Snowflake, Vector DBs, Apache Airflow, Kubernetes, AWS/GCP services.

What we offer

• Competitive base salary $185,000‑$215,000 per year plus annual corporate bonus and long‑term incentive bonus.
• Premium health coverage, 401(k) with generous matching, financial planning resources, paid time off, parental leave, life and disability protection.