Sensing Systems Lead Manager - Autonomous Drive (Hybrid)

General Motors Corporation; Sunnyvale (CA); Hybrid; USD 189,000 - 291,000; Full time

Benefits offered by this job

Company vehicle program

Relocation benefits

Hybrid/Remote work

Job summary

General Motors seeks a Technical Lead Manager for Sensing Systems Design & Validation in Sunnyvale, CA. You will define how camera, LiDAR, and RADAR sensing are characterized, simulated, integrated, and validated, shaping architecture decisions for safe, scalable autonomy.

You will lead a teams across sensing, perception, ML, simulation, and vehicle software, building tools and datasets to drive data-driven decisions and reduce technical risk.

Qualifications

• Bachelor's degree in computer science, computer engineering, electrical engineering, systems engineering, robotics, mathematics, or a related technical field.
• Ten or more years of progressive experience in software engineering, systems engineering, ML, perception, robotics, autonomous vehicles, or related field.
• At least 1 year of experience leading a small team of engineers.
• Experience leading complex technical initiatives spanning multiple disciplines.
• Experience designing, building, or integrating simulation, evaluation, validation, or data-processing systems for autonomy or safety-critical domains.
• Strong programming in C++ and Python with production-quality software, testable interfaces, debugging, and automation.
• Experience with ML workflows and frameworks like PyTorch or TensorFlow.
• Understanding of camera, LiDAR, RADAR, or multimodal sensing systems and related trade-offs.
• Experience using data, statistics, and structured experimentation to evaluate system behavior and decisions.
• Ability to communicate complex technical concepts in reviews, docs, and cross-functional discussions.
• Experience in iterative software development, code review, testing, version control, and agile planning.
• Demonstrated experience leading, coaching, or managing engineers and fostering an inclusive, high-performing team environment.

Responsibilities

• Set the technical direction for sensing-system evaluation frameworks measuring performance, robustness, and scalability.
• Lead integration of camera, LiDAR, RADAR, and sensor models into simulation and evaluation environments.
• Define fidelity, performance, and usability targets for large-scale experimentation.
• Develop statistical and empirical methods to supplement physics-based analysis.
• Generate and manage synthetic data from road-data replay, simulation, and scenario-generation pipelines.
• Design data augmentation and scenario coverage for challenging conditions (night, rain, snow, fog, occlusion, glare).
• Lead model retraining or pipeline demos to reduce end-to-end technical risk.
• Integrate new sensor components into autonomous driving software stack.
• Define and improve developer tools for sensing experiments (APIs, CLI, notebooks, dashboards).
• Develop evaluation metrics and reporting connecting sensor performance to system requirements and safety objectives.
• Lead technical reviews and cross-domain initiatives across teams.
• Identify opportunities to improve software architecture, test coverage, data quality, automation, and productivity.
• Mentor engineers and raise the bar for software quality and ownership.
• Hire, coach, develop, and retain a high-performing team while ensuring delivery.

Skills

C++

Python

Production-quality software

Testing & debugging

Automation

Machine learning workflows

PyTorch

TensorFlow

Sensor systems knowledge

ROS / robotics middleware

Education

Bachelor's degree in CS/CE/Robotics or related field

Tools

ROS

Linux

Containers

CI/CD

Distributed computing

Cloud platforms

BigQuery

Job description

General Motors seeks a Technical Lead Manager for Sensing Systems Design & Validation in Sunnyvale, CA. You will define how camera, LiDAR, and RADAR sensing are characterized, simulated, integrated, and validated, shaping architecture decisions for safe, scalable autonomy.

You will lead a teams across sensing, perception, ML, simulation, and vehicle software, building tools and datasets to drive data-driven decisions and reduce technical risk.