Senior Algorithm Engineer, Deep Learning & Vision at Bot Auto (Houston, TX / San Francisco, CA)Senior Algorithm Engineer, Deep Learning & Vision

Company Introduction

At Bot Auto, we are revolutionizing the transportation of goods with our cutting-edge autonomous trucks, enhancing the quality of life for communities around the globe. With the agility of a start-up and the wisdom of seasoned experts, Bot Auto boasts a team that has achieved numerous world-firsts and unparalleled innovations. United by a shared vision, we create miracles and propel the future of transportation. Join us and transform your dreams into reality.

• Explore and propose new ideas using your knowledge and experience in deep learning, neural networks and large foundation models in autonomous driving including: end-to-end object detection, tracking and prediction, end-to-end planning and control, and end-to-end autonomous driving system, end-to-end online mapping. SLAM in localization and etc..
• Work on the entire life cycle of machine learning projects from data analysis, model experimentations to performance metrics verifications, and understand the entire workflow in great detail.
• Be exposed to many cross-team projects and collaborate with the product, simulation and other sibling autonomous driving algorithm teams to extend machine learning technology to all components.

Required:

• Have an advanced degree (Ph.D or Master’s) in related fields of study: computer science, computer engineering, robotics, mathematics, physics, and etc.
• Have in-depth knowledge and extensive experience in machine learning, and/or computer vision, modern transformer architecture, and employ SOTA techniques of machine learning.
• Be familiar with PyTorch, TensorFlow and other machine learning platforms and tools.
• Have strong motivation to work independently in a fast paced environment while collaborating with other teams on more complex and larger projects.

Preferred:

• Have a proven track record of research publications in top conferences and/or journals as the first author.
• Have knowledge and experience of generative models, model distillation, or model inference acceleration (e.g. TensorRT) techniques.