Machine Learning Engineer - Prediction

Motional•Boston, MA

68d•Remote

About The Position

Join us in shaping the future of autonomous driving. As part of the Behaviors team, you will work alongside world-class ML engineers and research scientists to help make self-driving vehicles a safe, reliable, and transformative reality. Our team builds the intelligence responsible for understanding complex driving environments and generating safe and comfortable trajectories for our robotaxi fleet using cutting-edge deep learning and planning systems. We welcome fresh graduates who are passionate about robotics, machine learning, and autonomous systems — and eager to grow in a fast-moving, high-impact team. This opportunity can support remote work within the United States, with occasional travel.

Requirements

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.

Nice To Haves

Publications in relevant conferences (CVPR, ICML, NeurIPS, ICCV, ECCV, ICRA, IROS etc.)
Project or internship experience on VLM, VLA and other foundation models for robotics and self-driving.
PhD in machine learning, generative AI, computer vision, or robotics vision
Project experience working on autonomous vehicles or related fields
Experience in deploying models into real-world environments
Strong programming skills in C++ and/or CUDA programming

Responsibilities

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