Staff Perception Algorithm Engineer
Posted on 1/9/2024
INACTIVE
XPeng Motors

1,001-5,000 employees

Designs and manufactures intelligent electric vehicles and aircrafts
Company Overview
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.
Data & Analytics
Robotics & Automation
Hardware
Consumer Software
AI & Machine Learning

Company Stage

N/A

Total Funding

$8.2B

Founded

2014

Headquarters

Guang Zhou Shi, China

Growth & Insights
Headcount

6 month growth

-11%

1 year growth

-6%

2 year growth

17%
Locations
Santa Clara, CA, USA • San Diego, CA, USA
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Data Structures & Algorithms
Computer Vision
CategoriesNew
AI & Machine Learning
Requirements
  • Ph.D in EE, CS or related field with 3 years, or Masters with 5 years full time work experience in algorithms design
  • Solid background in computer vision, image processing, 3D geometry, estimation, non-linear optimization
  • Proficient in developing in C++
  • Hands on experience in one of the following: visual odometry, camera calibration, 3D reconstruction, maps
  • Strong mathematical foundation
Responsibilities
  • Research and develop algorithms for ego pose tracking and static environment tracking using semantic features from cameras, lidar, inertial and other sensors
  • Collaborate with AI model teams to build a 3D perception pipeline
  • Work closely with cross functional team for rapid execution on target platforms
Desired Qualifications
  • Experience in map-less self-driving product for driving / parking in urban environments
  • Experience with transformer based BEV nets and occupancy tracking