Search the 25 jobs at XPeng Motors

The Machine Learning Engineer will research, develop, and optimize perception algorithms for autonomous vehicles, focusing on deep learning and computer vision. Responsibilities include training large-scale models, improving algorithm performance, and collaborating on software development and testing.

The Computer Vision Intern will design and implement advanced vision algorithms for autonomous driving, conduct research on cutting edge vision models, test and optimize algorithms, and collaborate with cross-functional teams on product development and integration.

The Staff Machine Learning Engineer will design, train, and deploy large deep learning models, leveraging data from millions of vehicles to solve the autonomous driving problem. You will collaborate with a team of engineers and scientists to develop state-of-the-art machine learning infrastructure and accelerate model training and inference.

The Senior Machine Learning Engineer will design, train, and deploy large deep learning models that use extensive labeled and unlabeled data from a fleet of vehicles. This role involves working with a team to establish a cutting-edge ML infrastructure for training large foundation models and accelerating model training/inference, specifically for autonomous driving solutions.

As a Machine Learning Intern at XPeng Motors, you will work on developing advanced deep learning models for autonomous driving, collaborating with researchers to create AI software systems and improving machine learning solutions for perception tasks like object detection and segmentation.

As a Machine Learning Engineer at XPeng Motors, you will fine-tune LLMs for use in humanoid robots and autonomous driving technology, develop scalable training and deployment pipelines, and explore synthetic data generation. Collaboration with multiple teams and the opportunity to influence product development are key aspects of the role.

Design and implement ML infrastructure for training large foundation models at XPeng Motors, focusing on autonomous driving solutions. Collaborate with engineers and scientists to enhance model training and inference speed with extensive data from vehicles.

The AI Performance Engineer will optimize the training and inference performance of machine learning models for autonomous driving, working on NVIDIA GPU systems. Responsibilities include reducing latency for model inference and processing workloads, alongside a focus on deep learning infrastructure optimization.

The Machine Learning Engineer at XPeng Motors will design, train, and deploy deep learning models using data from a fleet of vehicles. This role involves establishing ML infrastructure for large foundation models and accelerating their training and inference, collaborating with engineers and scientists to improve autonomous driving solutions.

The Senior Machine Learning Engineer will research, prototype, optimize, and deploy advanced perception algorithms for autonomous vehicles. Responsibilities include training large deep learning models, optimizing compute resources, and collaborating with software and test teams.

As a Staff Machine Learning Engineer, you will design and implement deep learning algorithms using labeled and unlabeled data to advance autonomous driving technologies. You will collaborate with researchers and developers to integrate the latest research into production, focusing on large language models and foundation models.

The role involves analyzing, designing, and implementing software solutions for autonomous driving, focusing on building performance-critical frameworks and libraries in C++. It includes mentoring junior developers and collaborating across teams to enhance software architecture and resolve performance bottlenecks.

As a Senior Software Engineer for XPeng Motors, you will analyze, architect, design, and implement software solutions to enhance development productivity. Your role will involve deploying new tools, developing scripts, and maintaining pipelines. You will also debug and resolve issues across all environments.

The Senior Staff Machine Learning Engineer will research and implement AI methodologies to enhance productivity, mentor engineers, and shape the vision for AI applications. Responsibilities include investigating AI solutions for code optimization, automation of workflows, and collaboration with cross-functional teams.

The Staff Software Engineer will develop big data applications for ADAS, work on systems like ETL pipelines and inference platforms, collaborate with ML engineers, and handle requirements analysis, system design, and cloud deployment.

As an AI Infrastructure Engineer, you will enhance productivity by addressing infrastructure gaps, developing scalable AI/ML solutions, and optimizing performance within GPU clusters. Your role involves collaboration with ML teams and implementing automation tools to streamline operations.

As a Machine Learning System Engineer Intern, you will research and build machine learning solutions for autonomous driving, working with various models, datasets, and cross-functional teams to enhance performance in perception tasks.

The Perception Algorithm Engineer will contribute to the development of a map-less self-driving product, focusing on ego-localization and static environment modeling. Key responsibilities include researching algorithms, collaborating with AI teams, and executing projects across platforms.

The Senior Machine Learning Engineer will develop advanced algorithms for humanoid robotics using imitation learning and reinforcement learning. Responsibilities include designing machine learning models, optimizing training processes, and contributing to team collaborations to push the boundaries of robotics technology.

Seeking a Senior Staff Perception Algorithm Engineer at XPeng Motors to work on map-less self-driving products for urban environments. Responsibilities include developing algorithms for ego pose tracking and static environment tracking using advanced technologies and collaborating with cross-functional teams for rapid execution. Requires a Ph.D. in EE, CS or related field with 5 years of experience or a Master's with 8 years of full-time work experience in algorithms design.