Member of Technical Staff, Computer Vision (Perception)

Physical AI runs on data that captures how the real world looks, moves, and fits together in 3D. As a perception-focused Machine Learning Engineer at Sieve, you'll build the systems that turn raw egocentric, robot, and sensor footage into the training data that robotics and world-model teams depend on.

You'll bring the computer vision instincts of someone who has shipped perception for robots, devices, or autonomous vehicles, and apply them to datasets at a scale few teams ever touch. One week you might recover camera pose and scene geometry across thousands of hours of first-person video. The next, you might build a hand and object tracking pipeline, or design a benchmark that tells a lab whether their data actually improves manipulation policies.

• Build perception pipelines for depth, pose, tracking, segmentation, and 3D reconstruction over large video and multi-sensor datasets
• Apply SLAM, visual odometry, and structure-from-motion to recover camera trajectories and scene geometry at scale