Our Machine Learning (ML) team is looking for world-class research scientists and engineers to turn Toyota’s data advantage into an AI advantage. As the #1 car maker in the world with 100 million cars on the road today, we can learn from massive amounts of data to realize safe automated driving on a global scale. Our team’s mission is to use all the data to identify and solve open research problems on the critical path to automated driving. We are working on some of the hardest challenges in the area of perception (e.g., scene understanding, 3D vision, tracking), prediction (e.g., handling uncertainty, predicting human behavior, trajectory forecasting), planning (e.g., understanding and reacting to human intent, multi-agent modeling), and general machine learning (e.g., self-supervised learning, imitation learning, active learning, multi-task learning, domain adaptation, robustness to the heavy tail of edge cases, efficient deep learning, large scale distributed training). We invent new Deep Learning algorithms that can leverage massive amounts of data (labeled or not), experimentally showing state-of-the-art performance (both in internal benchmarks and public ones, publishing at top Machine Learning and Computer Vision conferences and collaborating with our university partners). We work closely with other teams at TRI to transfer and ship our most successful algorithms and models towards world-scale long-term autonomy.
As a Machine Learning Engineer, you will contribute to state-of-the-art machine learning infrastructure and relevant software (e.g. distributed training, continuous model integration, data management, and evaluation at unparalleled scale). You will implement cutting-edge deep learning models accelerating model training time, improving performance, and tackling open problems together with research scientists. Last but not least, you will deploy your algorithms and models in our self-driving test vehicles and beyond. Responsibilities and required qualifications are as follows: