Who we are

Aurora’s mission is to deliver the benefits of self-driving technology safely, quickly, and broadly.

The Aurora Driver will create a new era in mobility and logistics, one that will bring a safer, more efficient, and more accessible future to everyone.

At Aurora, you will tackle massively complex problems alongside other passionate, intelligent individuals, growing as an expert while expanding your knowledge. For the latest news from Aurora, visit aurora.tech or follow us on LinkedIn.

What we are looking for

Aurora hires talented people with diverse backgrounds who are ready to help build a transportation ecosystem that will make our roads safer, get crucial goods where they need to go, and make mobility more efficient and accessible for all.

We are seeking a Software Engineer and Machine Learning practitioner to join the Perception Tracker Team at Aurora. In this role, you will play a critical part in elevating the Aurora Driver’s perception performance and support the expansion of our driverless operational domain across key routes throughout the United States. Your work will be fundamental to scaling our mission, directly contributing to the delivery of self-driving benefits safely, quickly, and broadly.

In this role you will

Tackle end-to-end perception challenges, including tracking dynamic actors, recognizing actions and attributes, and developing deep semantic understanding of diverse traffic environments.

Research and develop state-of-the-art machine learning models to enhance perception performance in challenging, real-world scenarios, such as highway versus urban driving, long-range multi-sensor tracking, varying weather conditions, and degraded sensor conditions.

Collaborate cross-functionally to iterate on the Perception system, translating insights from on-road and simulated testing into robust, high-quality, and well-tested software solutions.

Drive the software development lifecycle from prototype to production, focusing on large-scale data analysis and the deployment of performing, production-ready solutions on the real-time Aurora Driver platform.

Contribute to architectural strategy and team collaboration, ensuring our perception systems remain scalable, efficient, and at the forefront of autonomous driving technology.

Example projects that a candidate could potentially contribute to (list not exhaustive):

Design and implement state-of-the-art object tracking algorithms.

Design algorithms to extract, leverage, and fuse complementary information from different sensors.

Design and implement state-of-the-art ML systems for object tracking and object attribute classification leveraging expertise in recursive state estimation, Hidden Markov models, structured prediction, and sequential models.

Build and improve model pipelines for large-scale and efficient model training.

Analyze failure modes and implementation/testing of solutions to address the surfaced issues

Required qualifications

Master's degree or higher in Computer Science, Robotics, Electrical Engineering, or a related field (or Bachelor with 1+ years of relevant industry experience in software engineering).

Proficient software engineering skills in C++ and Python, with a focus on writing clean, scalable, and efficient production-quality code.

Basic knowledge in one or more focus areas: deep learning, computer vision, recursive state estimation, structured prediction, numerical optimization, and others.

Basic knowledge about 3D object tracking algorithms.

Experience with PyTorch, Tensorflow, and/or other deep learning frameworks

Desirable qualifications

Strong grasp of fundamentals: linear algebra, discrete and continuous optimization, supervised and unsupervised methods, generative and discriminative methods, and Hidden Markov Models.

Hands-on experience with VLM, foundational or world models.

Hands-on experience in CUDA or high-performance GPU programming for accelerated computing.

Experience with deploying production-grade CV/ML models within real-time computing environments.