Senior Software Engineer, Perception

Aurora•Mountain View, CA

1d•Hybrid

About The Position

Aurora is seeking a Senior Software Engineer, Perception to join its autonomous driving team. The role collaborates with cross-functional engineering teams to design and deploy state-of-the-art machine learning models on Aurora’s real-time vehicle platform, addressing complex autonomy challenges and advancing the Aurora Driver. The engineer will develop perception models for challenging scenarios, including long-range multi-sensor detection and degraded sensor conditions. The work spans object detection, traffic-actor tracking, action recognition, and semantic understanding of traffic scenes. The role guides software from prototype through production deployment, uses large-scale datasets for training and analysis, investigates failures from on-road and simulated testing, and builds scalable machine-learning pipelines for experimentation, training, and testing. Aurora expects employees to work from the office at least three days per week; some roles may require more frequent in-office work, up to five days per week, based on operational needs. Employees are expected to follow safety policies and contribute to a safe working environment. The position offers a base salary range of $162,000–$260,000, with eligibility for an annual bonus, equity compensation, and benefits.

Requirements

BS, MS, or PhD in Computer Science, Robotics, Engineering, or a related field, with a strong foundation in one or more machine-learning focus areas, including deep learning, computer vision, recursive state estimation, structured prediction, and optimization.
At least 6 years of research-based or professional experience with C++ and Python.
Comprehensive understanding of linear algebra, discrete and continuous optimization, supervised and unsupervised methods, and generative and discriminative models.
A strong publication record at top-tier robotics or computer-vision conferences or journals, or significant industry experience in a relevant field such as robotics, computer vision, or self-driving technology.

Nice To Haves

Experience using deep-learning frameworks such as PyTorch or TensorFlow.
Advanced production-level knowledge of C++ is highly preferred.
Prior experience applying computer vision and machine learning to complex robotics problems.
Experience deploying computer-vision or machine-learning models at scale across large physical fleets.
Demonstrated ability to work effectively in environments requiring close cross-team collaboration.
Experience with 3D data, including 3D object detection, tracking, semantic segmentation, or processing point clouds from LiDAR, Radar, and multi-camera systems.

Responsibilities

Research and develop deep-learning and machine-learning models to improve perception in challenging scenarios, including long-range multi-sensor detection and degraded sensor conditions.
Address object detection, tracking of traffic actors, action recognition, and semantic understanding of diverse traffic scenes.
Guide software development from prototype through production deployment on a real-time autonomous-vehicle platform.
Use large-scale datasets for model training and analysis.
Collaborate with team members to diagnose, analyze, and resolve failure modes identified during on-road and simulated testing.
Build and scale machine-learning pipelines for rapid experimentation and large-scale training and testing.