Search the 23 jobs at XPeng Motors

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 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 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 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.

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 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 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.

The role involves researching and implementing deep-learning methods for legged locomotion in humanoid robots, developing motion controllers using reinforcement learning, and analyzing experiments to improve RL controllers in real-world scenarios.

The Staff Machine Learning Engineer will design, train, and deploy large deep learning models utilizing labeled and unlabeled data from a fleet of vehicles, advancing autonomous driving technologies. This role includes establishing ML infrastructure and accelerating model training/inference with a focus on transformer architecture.

As a Senior Machine Learning Engineer, you will design, train, and deploy large deep learning models to utilize vast data from a fleet of vehicles, establishing a state-of-the-art ML infrastructure. You will work collaboratively with a team to solve the autonomous driving problem by pushing the boundaries of machine learning technology.

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 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.