Senior AI Systems Engineer- Autonomous Driving

Skills this role screens for

About the role

In this role, you will operate as a Senior 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.

The work

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.

Nice to have

Preferred Qualifications

We offer a competitive base salary for this position with a range in US-California of --$185,000 - $215,000 along with an annual corporate bonus, and a long-term incentive bonus designed to reward sustained impact and contribution over time. Within the salary range, the individual pay is determined based on several factors, including, but not limited to, work experience and job knowledge, complexity of the role, job location, etc.

Your well-being matters at Bosch! We offer a a benefits package designed to empower you in every area of your life. This includes premium health coverage, a 401(k) with generous matching, resources for financial planning and goal setting, ample paid time off, parental leave, and comprehensive life and disability protection.  Your Recruiter can share more details for this position during the interview process.

Learn more about our full benefits offerings by visiting: https://www.myboschbenefits.com/public/welcome.

Equal Opportunity Employer, including disability / veterans.

*Bosch adheres to Federal, State, and Local laws regarding drug-testing. Employment is contingent upon the successful completion of a drug screen and background check. Candidates who have been offered the position must pass both screenings before their start date.

#LI-JM1

• 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.