About Xpeng
XPENG is a leading technology company focused on designing, developing, manufacturing, and marketing intelligent mobility solutions, including electric vehicles (EVs), electric vertical take-off and landing (eVTOL) aircraft, and robotics. We aim to create a thoughtful and empathetic future for mobility that enhances driving experience. Headquartered in Guangzhou, China, XPENG has regional offices in Beijing, Shanghai, Shenzhen, Silicon Valley, and San Diego. In 2021, we established our European headquarters in Amsterdam, along with additional offices in Copenhagen, Oslo, and Stockholm, followed by the launch of our European R&D Center in Munich in 2025.
Our passionate and diverse team brings together expertise across technology, finance, and the automotive industry, spanning hubs in China, the United States, and Europe. Together, we are building our international presence as pioneers shaping the future of mobility.
Open Position
We are looking for a motivated student to join a paid, onsite 6-month Master’s thesis project starting in July at XPENG European R&D Center in Munich, focusing on generative AI. The student will become part of the AI Model Team and work under the supervision of experts in NLP and Audio Machine Learning.
The project explores how generative audio methods can be used to create realistic background noise and spatial acoustic conditions for data augmentation and controlled evaluation.
This opportunity is well suited for students with a strong interest in speech processing, audio machine learning, and generative AI.
Overview and Motivation
Modern multimodal voice assistants rely on large, high-quality speech datasets recorded in diverse acoustic environments. However, collecting and curating such real-world data is both costly and time-consuming, and often fails to sufficiently cover important edge cases and environmental variations.
Recent advances in generative AI for audio have enabled the synthesis of realistic and controllable acoustic environments, including background noise and spatial sound characteristics. This thesis investigates whether these generative methods can be leveraged to augment or partially replace traditional data collection approaches. The goal is to evaluate whether synthetic acoustic environments can improve model robustness and downstream performance in controlled evaluation settings, thereby enhancing the overall quality of multimodal voice assistants.
Details
* Topic: Exploring Generative AI for Synthetic Acoustic Environment Creation in Multimodal Voice Assistant
* Position Type: Paid Master’s thesis
* Location: XPENG European R&D Center, Weimarer Str. 32, 80807 Munich (on-site, 30 hours per week)
* Team: AI Model Team
* Supervision: Guidance from experts in NLP and Audio Machine Learning
* Duration: 6 months (starting July)
XPENG offers:
* 6-Month Paid Master Thesis Position
* An exciting, unique, and highly diverse role with opportunities at XPENG
* The opportunity to contribute to the growth of an established EV brand in Europe
Next steps:
To comply with GDPR, we are unable to process your personal data without your explicit consent. Therefore, please submit your application directly via LinkedIn so that our team can proceed with the next steps.
Our Commitment to Diversity and Inclusion: At XPENG, we are an equal opportunity employer and value diversity. We strongly encourage applications from suitably qualified candidates regardless of race, religion, sex, national origin, gender identity, sexual orientation, age, marital or marital status, disability, or any other characteristics protected by applicable law.