This role pays less than
52%
of similar roles. Most pay
$162,000–$238,725
— the shaded band above.
At the midpoint, this role pays about
$200k
versus about
$200k
for comparable roles.
Based on 240 similar postings.
Employer
About Bosch
Bosch is a global engineering and technology company supplying mobility solutions, industrial technology, consumer goods, and energy and building technology; Robert Bosch LLC is its North American arm.
Bosch currently has
34 open roles
on FindRole.
Listed pay typically runs
$165,000–$185,000
across 16 roles with salary data.
As a Staff AI Systems Engineer- Autonomous Driving, you will join a cross-functional team to set technical direction, influence architecture, and elevate engineering standards for autonomous driving technologies. You will lead the design and implementation of AI-focused systems engineering and testing frameworks, specifically focusing on Advanced Driver Assistance Systems. Your daily work involves architecting scalable failure triaging and automated Root Cause Analysis frameworks to process petabyte-scale simulation and vehicle logs. You will apply LLMs, VLMs, time-series anomaly detection, and causal inference to isolate failure modes across perception, planning, and control layers. Key technologies include Python, C++, ROS/ROS2, MCAP, Protobuf, and CAN logs, alongside distributed frameworks like PySpark, Ray, Databricks, and Kubernetes. You will integrate these automated diagnostics into SiL, HiL, and ViL cloud replay pipelines.
Architect and scale intelligent failure triaging and automated Root Cause Analysis frameworks for petabyte-scale logs.
Apply AI/ML methods 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.
Establish best practices for log data structures, automated analytics workflows, and vector search for failure retrieval.
Partner with autonomy software leads and cloud infrastructure teams to align toolsets and integrate automated diagnostics.
Guide the design, implementation, and evaluation of ADAS and Autonomous Driving technologies.
Set technical direction and engineering standards across multiple cross-functional teams.
What we're looking for
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 experience building production-grade data pipelines, distributed execution frameworks, or testing infrastructure.
Hands-on experience with big data structures, robotics logging formats (e.g., ROS/ROS2, MCAP, Protobuf, CAN logs), and cloud data storage.
Demonstrated experience applying LLMs/VLMs, sequence modeling, pattern recognition, or vector embeddings to log classification or automated root cause analysis (preferred).
In-depth understanding of autonomous driving software architectures including perception, sensor fusion, localization, motion planning, and vehicle control (preferred).
Experience with SiL, HiL, or cloud-based replay and simulation testing setups at scale (preferred).
TensorRT
CUDA
C++
Python
PyTorch
ONNX
Triton
Deep Learning Inference
Model Optimization
Quantization
Pruning
Linux
ISO 26262
QNX
Real-time Systems
DriveOS
Hypervisors
Python
C++
Linux
Docker
Kubernetes
CI/CD
Deep Learning
Computer Vision
Neural Rendering
3D Gaussian Splatting
NeRFs
Ray Tracing
OpenDRIVE
Sim-to-Real
Synthetic Data Generation