Machine Learning Engineer, Motion Planning & Prediction

OverviewMachine Learning Engineer, Motion Planning & Prediction at Avride. Join to apply for the Machine Learning Engineer, Motion Planning & Prediction role at Avride.About The TeamOur team develops the core software and data processing systems that power motion planning and decision-making in autonomous vehicles. We work at the intersection of machine learning, large-scale data infrastructure, and real-time vehicle control, collaborating across engineering, analytics, and product teams to deliver safe and intelligent driving capabilities.About The RoleWe are looking for a creative & driven Machine Learning Engineer to join our autonomous vehicle team. You will be at the center of our efforts to build intelligent systems that can understand, predict, and safely navigate a complex and dynamic world. This role involves designing and training the next generation of deep learning models that form the brain of our vehicle, learning from petabytes of real-world driving data. If you are passionate about applying cutting-edge ML to solve high-stakes robotics challenges, we want to hear from you.What You/'ll DoDesign, train, and deploy state-of-the-art machine learning models for behavioral prediction and motion planningDevelop robust data pipelines to process, clean, and label massive-scale vehicle sensor and simulation datasetsWork with deep learning architectures such as transformers to model complex temporal interactions between traffic agentsEstablish and own the metrics for model performance, and create evaluation frameworks that correlate with on-road safety and performanceCollaborate with software engineers to integrate and optimize trained models for real-time inference on the vehicles embedded hardwareStay current with the latest research in machine learning, imitation learning, and reinforcement learning, and apply novel techniques to our systemsWhat You/'ll NeedBachelor’s or Master’s degree in Computer Science, AI, Statistics, or a related technical fieldStrong proficiency in Python and hands-on experience with modern deep learning frameworks (e.g., PyTorch, TensorFlow, or JAX)Solid understanding of machine learning fundamentals, including various neural network architectures, training methodologies, and evaluation techniquesExperience with the full machine learning lifecycle, from data exploration and prototyping to deployment and monitoringProficiency in C++ for writing high-performance model inference codeNice to HaveA strong track record in ML competitions (e.g., Kaggle) or contributions to major open-source ML projectsExperience applying ML to problems in robotics, such as behavioral prediction, motion planning, or computer visionExperience with MLOps tools and platforms (e.g., MLflow, Kubeflow, Weights & Biases)Experience with large-scale distributed data processing and training frameworks (e.g., Spark, Ray)Publications in top-tier ML or robotics conferences (e.g., NeurIPS, ICML, CVPR, ICLR, CoRL, RSS)Candidates are authorized to work in the U.S. The employer is not offering relocation sponsorship, and remote work options are not available.OtherAustin, TX #J-18808-Ljbffr

Created: 2025-10-08