SLAM Engineer

Quidient is a deep tech AI company pioneering advancements in Generalized (5D) Scene Reconstruction (GSR). GSR is poised to become one of the world’s great digital product categories (think GPS, MRI, and LMM). Our flagship GSR product, Quidient Reality®, is a powerful API that enables anyone with a mobile device to virtualize, visualize, and measure anything. Words relevant to Quidient include Generative AI, Physics-Informed AI, Large Scene Models (LSMs), Large World Models (LWMs), and API-First.

Overview

Quidient is hiring a SLAM Engineer to advance the on-device visual-inertial SLAM system that powers our mobile capture experience. This role is central to how everyday users capture the world using their phones. You will enhance the live tracking pipeline running on mobile, pushing the limits of accuracy, robustness, and real-time AR visualization across a wide range of real-world scenarios — going well beyond what platform-provided solutions can deliver.

This is a hybrid position, meaning that you will need to live within easy driving distance to our Technology Center in Columbia, Maryland.

What You’ll Do

Real-time SLAM & Sensor Fusion

• Develop and advance our on-device visual-inertial odometry and VI-SLAM pipeline — including sensor fusion across multi-camera streams, IMU, and depth — with drift correction and relocalization for production capture workflows.
• Improve robustness across the full range of real-world user behavior — low-light, fast motion, textureless environments, and difficult geometry.
• Drive down latency and memory footprint on mobile hardware, offloading compute to GPU where possible. Direct experience with GPU programming (Metal shaders, CUDA kernels, or equivalent) is a strong advantage.
• Develop and extend calibration pipelines covering camera intrinsics, extrinsics, IMU biases, and time synchronization across multi-sensor mobile configurations.

Research Integration & Evaluation

• Collaborate with the team’s deep learning expertise to evaluate and selectively integrate learning-based methods alongside classical components in the live tracking stack.
• Build and extend evaluation methodology grounded in real user captures.
• Translate research progress into shipped capability in a fast-moving environment.

What You Bring

Must-Have Qualifications:

• Master’s, or PhD in Computer Science, Computer Vision, Robotics, or a related field — or equivalent demonstrated experience.
• Significant hands-on experience developing or substantially improving a real-time visual-inertial odometry or VI-SLAM system, with a strong emphasis on camera-based pipelines.