Member of Technical Staff, Computer Vision (Perception)

Sieve is hiring a perception-focused Machine Learning Engineer to build systems that turn egocentric, robot, and sensor footage into training data for robotics and world-model teams. The role develops scalable perception pipelines, model fine-tuning, data quality systems, and benchmarks, and works with frontier labs and robotics teams to deliver production pipelines.

Responsibilities:

• 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
• Fine-tune vision and vision-language models for embodied tasks like hand-object interaction, activity understanding, and scene understanding
• Develop automated QA and filtering systems that catch calibration errors, sync drift, motion blur, and other data defects before they reach customers
• Create benchmarks and evaluation frameworks that measure how much a dataset improves downstream robotics and world-model performance
• Work directly with frontier labs and robotics teams to turn vague data requirements into production pipelines
• Ship fast, measure results, and iterate based on how the data performs in the real world