Visual SLAM Researcher - Production-Ready 3D Vision

DeepReach AI; San Francisco (CA); On-site; USD 150,000 - 210,000; Full time

Job summary

DeepReach AI, an early-stage physical AI company, builds data infrastructure for robot learning and collaborates with frontier AI labs, robotics firms, and leading universities. The role focuses on taking SLAM/VIO/SfM innovations from research to robust production pipelines across devices, with calibration, synchronization, and validation at the core.

You’ll partner with hardware teams to test on-site and push reliable spatial computing into real products.

Qualifications

• 3+ years of experience in SLAM or 3D vision (graduate research counts).
• Strong foundation in multi-view geometry and state estimation.
• Proven experience building, maintaining, or improving SLAM, VIO, and SfM systems.
• Proficiency in C++ and Python; familiarity with OpenCV, Ceres, GTSAM, COLMAP, Kalibr or similar.
• Highly hands-on and product-oriented: you turn algorithms into reliable production systems.

Responsibilities

• Own, maintain, and improve multiple SLAM/VIO/SfM pipelines across capture devices.
• Run rigorous multi-camera and IMU calibration and time synchronization.
• Turn algorithms into high-throughput offline pipelines with quality metrics.
• Build visualization and debugging tools for images, point clouds, and trajectories.
• Serve as a computer vision hub for pre-/post-processing, data validation, and labeling.
• Work closely with the hardware team on sensor calibration and on-site testing.

Skills

Multi-view geometry

State estimation

Hands-on debugging

Production systems

English communication

Tools

C++

Python

OpenCV

Ceres

GTSAM

COLMAP

Kalibr

PyTorch

FFmpeg

Rerun

Job description

DeepReach AI, an early-stage physical AI company, builds data infrastructure for robot learning and collaborates with frontier AI labs, robotics firms, and leading universities. The role focuses on taking SLAM/VIO/SfM innovations from research to robust production pipelines across devices, with calibration, synchronization, and validation at the core.

You’ll partner with hardware teams to test on-site and push reliable spatial computing into real products.