Full-Time
Senior Staff Planning Machine Learning Engineer
Posted on 4/9/2024
Designs and manufactures intelligent electric vehicles and aircrafts
Compensation Overview
$220,000 - $370,000Annually
Senior
Santa Clara, CA, USA + 1 more
- MS or PhD level education in Engineering or Computer Science
- Strong experience in applied deep learning
- 5 - 8 years + of experience working with DL frameworks such as PyTorch, Tensorflow
- Strong Python programming experience
- Solid understanding of data structures, algorithms, code optimization and large-scale data processing
- Excellent problem-solving skills
- Research and develop algorithms for deep-learning-based methods for prediction and planning
- Design efficient model architectures that can run in real-time on the computing platform of our vehicles
- Develop offline data-driven ML infrastructure for fast adaptation of the planning ML models
- Deliver on target planning SW and closely work with the perception team to achieve the most intelligent autonomous driving systems
- Work with massive field-testing data to continuously improve autonomous driving technologies
- Designing, running, and analyzing experiments and testing to evaluate the efficiency of our solutions on real-world data
- Partnering with system software engineering specialists to ship industrial strength ML models
- Communicating and collaborating with multi-functional teams
XPENG stands out as a leader in the tech industry, with its focus on intelligent mobility solutions such as electric vehicles and eVTOL aircraft, demonstrating a competitive edge in the rapidly evolving transportation sector. The company's proprietary Advanced Driver Assistance System (XPILOT) and intelligent operating system (Xmart OS) enhance the user experience by integrating technology and mobility, positioning XPENG as a pioneer in smart, people-first mobility. The company's culture fosters technological advancement, making it an exciting workplace for those passionate about shaping the future of transportation.
Company Stage
N/A
Total Funding
$8.2B
Headquarters
Guang Zhou Shi, China
Founded
2014