Computer Vision Engineer • Mid-Level

Who you are

You are an engineer excited to work on cutting-edge software products and solutions using state-of-the-art computer vision and deep learning. You have a solid foundation in areas like detection, classification, segmentation, or tracking—whether through previous roles, internships, or research—and you’re eager to apply those skills in an impactful, production-focused environment. You are curious, motivated, and ready to learn from experienced teammates. You enjoy solving challenging technical problems, asking thoughtful questions, and collaborating with others to build high-quality software. You are excited about contributing to the perception stack for self-driving vehicles and learning what it means to build technology for safety-critical, open-world applications.

What you'll do

In this role, you will contribute to the design, development, and improvement of perception components that support downstream modules within the autonomy system. You will help analyze perception system performance to identify areas for improvement and participate in efforts to address them. Working with teammates, you will explore creative approaches to “long-tail” challenges—experimenting with synthetic data, data mining techniques, or new model architectures. Depending on your background and interests, you may also help optimize and deploy models to the vehicle, ensuring they operate within the constraints of our onboard hardware and meet our functional requirements and interface specifications. You will interface with systems and safety engineers, test engineers, and data analysts to ensure appropriate requirements are met, contributing to a collaborative and innovative environment.

What we offer

Motional provides a dynamic work environment where you can grow your skills and contribute to groundbreaking technology in the autonomous vehicle space. You will have the opportunity to work alongside experienced professionals who are passionate about advancing the field of computer vision and deep learning. We encourage you to apply even if your experience doesn't match every requirement, as we value diverse perspectives and backgrounds.