At General Motors, the business problem is to redefine mobility through a human-centered design process, creating vehicles and experiences that are designed not just to be seen, but to be felt, with the goal of making driving safer, smarter, and more connected.
Requirements
- Deep hands-on experience with modern deep learning frameworks (e.g., PyTorch or TensorFlow) for training, experimentation, and debugging complex DNNs.
- Proven experience working with and fusing data from multiple sensor modalities (Camera, LiDAR, and/or Radar).
- Practical experience deploying and optimizing ML models for resource-constrained, real-time embedded systems.
- Demonstrated ability to drive model improvements through large-scale data analysis, error logging, and data curation.
- 5+ years of professional experience with a focus on Computer Vision, Deep Learning, and Perception in a production environment.
- BS, MS or PhD in Computer Science, Machine Learning, Robotics, or a related quantitative field.
- Expertise with Transformer-based models for 3D detection, tracking, and scene understanding.
Responsibilities
- End-to-End Model Lifecycle: Own the design, training, validation, and deployment of deep learning models for core perception tasks such as 3D Object Detection and Tracking, Real-time map detection, and Multi-Modal Sensor Fusion.
- Production Pipeline: Build and scale the ML training infrastructure, including data mining and loading, multi-stage training and evaluation, to streamline model development.
- Performance Optimization: Improve model performance through data iterations, parameter tunings, training strategy and architecture updates to produce reliable models that meet the strict real-time, low-latency requirements on the vehicle's embedded hardware.
- Model Debugging: Conduct rigorous, data-driven analysis to identify, debug, and resolve performance degradations and failures, specifically targeting long-tail and adversarial scenarios.
- Metric Definition: Define and implement robust model-level metrics to aid model development.
- System Integration: Work closely with the Safety, Systems, and other engineering functions to integrate Perception outputs.
- Own the end-to-end pipeline for safety-critical ML perception models, from initial research and large-scale data curation to optimization and real-time deployment on the vehicle's compute platform.
Other
- BS, MS or PhD in Computer Science, Machine Learning, Robotics, or a related quantitative field.
- 5+ years of professional experience with a focus on Computer Vision, Deep Learning, and Perception in a production environment.
- Travel requirements not specified, but relocation benefits may be available.
- General Motors offers a variety of health and wellbeing benefit programs, including medical, dental, vision, and more.
- Applicants in the recruitment process may be required to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment.
