Artificial Intelligence and Planning Software Developer

Responsibilities

• This role involves developing deep-learning-based methods for prediction and planning problems in the context of autonomous vehicles
• You will work with a team of experienced computer vision, AI systems, and software engineers to deliver world-leading performance on our autonomous vehicles
• You will be responsible for researching, implementing, and evaluating deep-learning-based methods for a mix of prediction and planning problems
• This includes designing efficient model architectures that can run in real-time on the computing platform of our vehicles
• Develop algorithms for deep-learning-based methods for prediction and planning
• Design model architectures for efficient real-time implementation
• Develop ML infrastructure for fast adaptation of planning models
• Work closely with the perception team to achieve intelligent autonomous driving systems
• Work with massive field-testing data to continuously improve autonomous driving technologies
• Design, run, and analyze experiments to evaluate solution efficiency
• Collaborate with software engineering specialists to ship ML models
• Communicate and collaborate with multi-functional teams

Full Description

Company Overview

Xpeng Motors is a leader in the development of smart electric vehicles. We aim to transform the future of transportation by advancing autonomous driving technologies.

We combine innovative technology with sustainable energy solutions to create a better mobility experience for our customers. Our commitment to in-house R&D and intelligent manufacturing sets us apart from other companies.

Job Description

This role involves developing deep-learning-based methods for prediction and planning problems in the context of autonomous vehicles. You will work with a team of experienced computer vision, AI systems, and software engineers to deliver world-leading performance on our autonomous vehicles.

You will be responsible for researching, implementing, and evaluating deep-learning-based methods for a mix of prediction and planning problems. This includes designing efficient model architectures that can run in real-time on the computing platform of our vehicles.

• Develop algorithms for deep-learning-based methods for prediction and planning.

• Design model architectures for efficient real-time implementation.

• Develop ML infrastructure for fast adaptation of planning models.

• Work closely with the perception team to achieve intelligent autonomous driving systems.

• Work with massive field-testing data to continuously improve autonomous driving technologies.

• Design, run, and analyze experiments to evaluate solution efficiency.

• Collaborate with software engineering specialists to ship ML models.

• Communicate and collaborate with multi-functional teams.