Post Job Free
Sign in

Computer Vision Engineer

Company:
Energize Group
Location:
Santa Clara, CA, 95053
Posted:
June 19, 2025
Apply

Description:

Our client is transforming the $3 trillion infrastructure construction industry through cutting-edge robotics and autonomous navigation. With over 100 robots already deployed globally, their mission is to automate repetitive, labor-intensive tasks and bridge the workforce gap in construction, solar installation, surveying, and more.

Now's your chance to be part of a fast-growing team that's redefining how construction gets done smarter, faster, and more accurately.

The Role

We're hiring a Senior Computer Vision Engineer to lead the development of advanced vision systems for autonomous ground robots. You'll focus on sensor calibration, point cloud processing, terrain analysis, and navigation-playing a key role in enabling real-time perception and decision-making on complex construction sites.

Responsibilities

Develop and optimize vision algorithms for calibrating cameras, LiDAR, and IMUs

Fuse sensor data and process point clouds for real-time environment mapping

Conduct terrain analysis for obstacle detection and navigation

Design algorithms for object detection, segmentation, and tracking

Build and maintain real-time vision pipelines for deployment on autonomous platforms

Collaborate cross-functionally to integrate vision systems into robotic workflows

Document methods, experiments, and outcomes

Requirements

Master's degree in Computer Science, Electrical Engineering, Robotics, or related field

7+ years of experience in computer vision or image processing, ideally in autonomous systems

Proficiency in C++ and Python

Strong knowledge of point cloud processing, sensor calibration, and tools like OpenCV and PCL

Understanding of machine learning models for perception tasks

Familiarity with tools like Git, JIRA, and vision system debuggers

Excellent problem-solving and communication skills

Bonus Points For

Experience with terrain segmentation and environmental modeling

Familiarity with ROS and real-time robotic systems

Background in SLAM and deploying on edge computing hardware

Permanent

Apply