You will collaborate with researchers to manage and execute a high volume of experiments while characterizing neural network performance. Additionally, you will document qualitative and quantitative results in technical reports and suggest process improvements for future research iterations.
Design and implement core behavior planning and trajectory generation systems for autonomous vehicles. Collaborate cross-functionally to integrate planners with perception and control modules while ensuring verifiable safety and real-time performance.
Develop productionized ML workflows and platform infrastructure for training, validating, and deploying neural networks. Build distributed data-processing pipelines, internal APIs, and CI/CD processes to enhance developer productivity.
Collaborate on improving AI models and iterating on novel research directions for unsupervised learning and perception. Develop and maintain deep learning tools and deploy algorithms onto internal and customer autonomous vehicle platforms.
Collaborate on improving AI models and iterating on novel research directions for unsupervised learning and perception. Develop and maintain deep learning tools and deploy algorithms onto internal and customer autonomous vehicle platforms.
Design and implement safe, scalable real-time software for mass-production autonomous vehicle systems. Collaborate with AI teams and vendors to optimize the AV stack and architect continuous learning systems for ML models.
Architect and design scalable ML infrastructure and services to handle large-scale training and massive datasets. Lead the end-to-end platform lifecycle while mentoring engineers and collaborating with cross-functional teams.
