vSLAM Engineer for Real-World Home Robots

Weave Robotics; San Francisco (CA); On-site; USD 120,000 - 180,000; Full time

Job summary

Weave is seeking a highly skilled 3D Perception & SLAM Engineer to build and maintain production-grade vSLAM and localization systems for robots operating in real homes. You will fuse cameras, IMUs, odometry, and other sensors to deliver accurate, real-time localization, while advancing sensor calibration and data fusion infrastructure.

The role spans both application and research aspects, pushing the boundaries of traditional localization with learned methods and ensuring robustness for dynamic

Qualifications

• 3+ years of vSLAM and vision-based localization in real-world robotics.
• Strong understanding of state estimation, sensor fusion, and probabilistic estimation.
• Experience calibrating and integrating cameras, IMUs, odometry, and LiDAR into robust perception pipelines.
• Proficient in C++ or Python; ROS experience is preferred.

Responsibilities

• Build production-grade vSLAM and localization by fusing cameras, IMUs, odometry, and sensors for real-time robot localization.
• Develop sensor infrastructure for calibration, synchronization, and data fusion across the robot platform.
• Own localization stack from core estimation to sensor integration for dynamic indoor environments.
• Explore new localization/mapping approaches, combining geometry with learned methods for production deployment.
• Optimize perception systems for robustness, efficiency, and power in home environments.
• Debug on real robots using logs, recorded data, simulation, and hardware to turn edge cases into improvements.

Skills

vSLAM

State estimation

Multi-sensor fusion

C++/Python

Tools

ROS

Embedded systems

High-performance inference frameworks

Job description

Weave is seeking a highly skilled 3D Perception & SLAM Engineer to build and maintain production-grade vSLAM and localization systems for robots operating in real homes. You will fuse cameras, IMUs, odometry, and other sensors to deliver accurate, real-time localization, while advancing sensor calibration and data fusion infrastructure.

The role spans both application and research aspects, pushing the boundaries of traditional localization with learned methods and ensuring robustness for dynamic