The internship focuses on end-to-end autonomous driving AI at XPeng, contributing to the development of their revolutionary autonomous driving platform. Interns will work in areas like machine learning, AI modeling, and software development to advance self-driving technology.

The internship involves working on data-driven manipulation, human-robot interaction using multi-modal LLM, and enhancing locomotion and navigation for robots using advanced controller techniques.

The Senior Staff Machine Learning Engineer at XPeng Motors will design, train, and deploy large deep learning models using vast amounts of data from vehicles. The role involves establishing advanced ML infrastructure for foundation model training and inference, collaborating within a skilled team to advance autonomous driving technology.

As a Senior Machine Learning Engineer at Xpeng Robotics Center, you'll develop advanced ML algorithms for humanoid robots, facilitating their interaction with the physical world. This role involves designing models, improving training processes, and contributing to interdisciplinary projects, with a focus on leveraging cutting-edge machine learning technologies.

The role involves researching and developing algorithms for ego pose tracking and static environment modeling for autonomous driving systems, utilizing advanced computer vision and machine learning techniques. It requires collaboration with cross-functional teams and a strong focus on software design and code quality.

The Director/Principal Engineer for Big Data will lead the development of XPeng's big data infrastructure to support autonomous driving innovation. Responsibilities include designing systems for data ingestion and processing, overseeing project management, establishing technical roadmaps, and collaborating with cross-functional teams to ensure high-quality data delivery.

The Staff Software Engineer will design and implement modules for the autonomous software stack, optimize system performance, debug issues, and provide software architecture guidance. This role demands excellent programming skills and extensive experience in software development.

As a Machine Learning Engineer, you will design, train, and deploy large deep learning models using vast amounts of data from vehicles. The role focuses on establishing state-of-the-art ML infrastructure for large foundation models, enhancing training and inference processes, while collaborating with a team of software and research experts in autonomous driving.

The Staff Software Engineer at XPeng Motors will design and implement tools and infrastructure to enhance the workflows of machine learning engineers, develop complex workflows to assess software quality, and utilize LLMs for process improvements. The role requires extensive experience in backend services and machine learning infrastructure.

The Junior Test Engineer will develop test cases for powertrain and charging systems, conduct testing in an agile environment, analyze CAN traces, and report on test results. The role requires coordination with various teams and requires an engineering degree, knowledge in programming, power electronics, and testing tools.

The Junior Test Engineer will execute test cases for ADAS systems, analyze results, report defects, collaborate with teams for system testing strategies, and support EU-NCAP and real vehicle tests, ensuring the effective validation of driver assistance technologies.

The Junior Test Engineer will develop and implement system test plans, create and maintain automated test scripts, execute and analyze test cases, and collaborate with development teams to address issues in the In-Car-Entertainment system. The role requires documenting testing phases and recommending improvements based on testing outcomes.

As a Perception Algorithm Engineer, you will research and develop algorithms for ego-localization and environment modeling for autonomous vehicles. Working closely with cross-functional teams, you'll build perception pipelines integrating various sensor data, ensuring the reliability of self-driving solutions.

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.

The role involves designing and operating components of an inference platform, identifying performance bottlenecks, collaborating with Machine Learning Engineers, and ensuring the reliability of the infrastructure through monitoring and system maintenance.

As a Senior Staff AI Infrastructure SRE at XPeng Motors, lead the design and implementation of robust cloud-native AI infrastructure solutions to support autonomous driving initiatives. Collaborate with ML teams, address system bottlenecks, and foster technological advancements. Minimum 5-8 years of experience in managing GPU clusters and strong programming skills in Python, Golang.

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.

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 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.