XPeng Motors is one of China’s leading smart electric vehicle (EV) companies. We design, develop, and manufacture smart EVs that are seamlessly integrated with advanced Internet, AI and autonomous driving technologies. We are committed to in-house R&D and intelligent manufacturing to create a better mobility experience for our customers. We strive to transform smart electric vehicles with technology and data, shaping the mobility experience of the future.

We are looking for a talented AI/ML Infrastructure Engineer to join our team. In this role, you will have the opportunity to improve productivity for our researchers by enhancing the entire stack. Your primary duty will be to identify and resolve infrastructure gaps to provide reliable, efficient, and scalable solutions.

Job Responsibilities:

Identify and resolve infrastructure gaps to ensure reliable, efficient, and scalable solutions
Develop advanced AI/ML infrastructure solutions that enhance the efficiency of our skilled ML teams
Design and implement solutions for critical areas, including distributed storage systems, scheduling systems, high availability capabilities, and core reliability issues within our large-scale GPU clusters
Monitor and optimize the performance of our AI/ML infrastructure, ensuring high availability, scalability, and efficient resource utilization
Develop and deploy automation tools, monitoring solutions, and operational strategies to streamline infrastructure management and reduce manual tasks
Work with various teams, including ML developers, data engineers, and DevOps professionals, to create a cohesive and integrated AI/ML infrastructure ecosystem

Minimum Skill Requirements:

Bachelor’s degree in Computer Science, Engineering, or related technical field
5-8+ years of experience in software engineering, with a strong background in developing and managing large-scale distributed systems, ideally within the AI/ML infrastructure domain
Proficiency in programming languages such as Python, Go, or C++, with knowledge of cloud computing platforms like AWS, Azure, etc.
Strong communication and collaboration abilities, effective in working with diverse teams and individuals

Preferred Skill Requirements:

In-depth understanding of AI/ML workflows, including model training, data processing, and inference pipelines
Practical experience with containerization technologies (i.e., Docker, Kubernetes), automation tools (i.e., Ansible, Terraform), and monitoring solutions (i.e., Prometheus, Grafana)
Exceptional problem-solving skills, capable of analyzing complex systems, identifying bottlenecks, and implementing scalable solutions
A passion for continuous learning and staying abreast of new technologies and best practices in the AI/ML infrastructure space

What do we provide:

A fun, supportive and engaging environment
Opportunity to make significant impact on the transportation revolution by the means of advancing autonomous driving
Opportunity to work on cutting edge technologies with the top talent in the field
Competitive compensation package
Snacks, lunches and fun activities

The base salary range for this full-time position is $180,000-$300,000, in addition to bonus, equity and benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.

We are an Equal Opportunity Employer. It is our policy to provide equal employment opportunities to all qualified persons without regard to race, age, color, sex, sexual orientation, religion, national origin, disability, veteran status or marital status or any other prescribed category set forth in federal or state regulations.

Staff AI Infrastructure Engineer

XPeng Motors

Compensation Overview

Job Responsibilities:

Minimum Skill Requirements:

Preferred Skill Requirements:

What do we provide: