Software Engineer, AI Engineer

Qualifications

• MS./Ph.D. in Computer Science/Electrical Engineering/Mechanical Engineering/Robotics or related disciplines
• Minimum 3–5+ years of software engineering experience
• Proficient in Python and C++
• Solid background in SLAM, computer vision, image processing, 3D geometry, estimation, and non‑linear optimization
• Hands‑on experience in visual odometry, camera calibration, 3D reconstruction, or mapping
• Strong mathematical foundation
• Strong will to research, develop, and apply deep learning algorithms to new problems
• Opportunity to make significant impact on the transportation revolution by advancing autonomous driving

Benefits

• A fun, supportive, and engaging environment
• Opportunity to work on cutting‑edge technologies with top talent in the field
• Competitive compensation package
• Snacks, lunches, and fun activities
• The base salary range for this full‑time position is $179,400 – $303,600, in addition to bonus, equity, and benefits
• Our salary ranges are determined by role, level, and location
• Within the range, individual pay is determined by work location and additional factors, including job‑related skills, experience, and relevant education or training

Responsibilities

• Research and develop algorithms for ego pose tracking and static environment tracking using semantic features from cameras, radar, inertial and other sensors
• Work closely with cross‑functional teams for rapid execution on target platforms

Full Description

Position: Staff Software Engineer

Staff Software Engineer

XPENG is a leading smart technology company at the forefront of innovation, integrating advanced AI and autonomous driving technologies into its vehicles, including electric vehicles (EVs), electric vertical take‑off and landing (eVTOL) aircraft, and robotics.

With a strong focus on intelligent mobility, XPENG is dedicated to reshaping the future of transportation through cutting‑edge R&D in AI, machine learning, and smart connectivity.

Job Responsibilities

• Research and develop algorithms for ego pose tracking and static environment tracking using semantic features from cameras, radar, inertial and other sensors.

• Work closely with cross‑functional teams for rapid execution on target platforms.

Job Requirements

• MS./Ph.D. in Computer Science/Electrical Engineering/Mechanical Engineering/Robotics or related disciplines.

• Minimum 3–5+ years of software engineering experience.

• Proficient in Python and C++.

• Solid background in SLAM, computer vision, image processing, 3D geometry, estimation, and non‑linear optimization.

• Hands‑on experience in visual odometry, camera calibration, 3D reconstruction, or mapping.

• Strong mathematical foundation.

• Strong will to research, develop, and apply deep learning algorithms to new problems.

Preferred

• Familiarity with a machine learning development framework such as PyTorch, Tensor Flow, or MXNet.

What We Provide

• A fun, supportive, and engaging environment.

• Opportunity to make significant impact on the transportation revolution by advancing autonomous driving.

• Opportunity to work on cutting‑edge technologies with top talent in the field.

• Competitive compensation package.

• Snacks, lunches, and fun activities.

The base salary range for this full‑time position is $179,400 – $303,600, in addition to bonus, equity, and benefits.

Our salary ranges are determined by role, level, and location.

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, marital status, or any other prescribed category set forth in federal or state regulations.

Seniority level

Associate

Employment type

Full-time

Job function

Motor Vehicle Manufacturing

Location:

San Diego, CA

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