Machine Learning Engineer - ML Planner

Masters or PhD in Machine Learning, Generative AI, Computer Science, Applied Mathematics, Statistics. In-depth understanding of common Machine Learning and Deep Learning algorithms, especially transformer-based architectures, autoregressive decoder architectures etc. Experience designing, training, and analyzing neural networks/transformer-based models for at least one of the following applications: motion planning, object detection, sensor fusion, motion prediction, and/or multi-object tracking, multi-agent predictions. Knowledge of software engineering principles, including software design, source control management, build processes, code reviews, and testing methods Knowledge or course experience of generative models such as VLM, VLA etc. Experience with PyTorch or other Python-based deep learning frameworks Experience working with large data sets, data curation, and augmentation.

Designing and training large models for predicting surrounding agents, AV behaviors, and end-to-end planning systems by executing high-value experiments based on collaborative input from other machine learning engineers Prototyping and implementing continuously improving metrics to evaluate the performance of our behavioral models across many desired scenarios and robotaxi capabilities Timely release of major model updates, including analysis of both off-line and on-road evaluation data Staying up to date with the latest trends in our fast-moving industry, and proposing new architectures and network designs Maintaining a high-quality training and evaluation code-base, including portions of our training stack dedicated to dataset generation and evaluation