Member of Technical Staff — Perception & 3D Vision

Sieve; San Francisco (CA); On-site; USD 150,000 - 220,000; Full time

Job summary

Sieve in San Francisco is seeking a perception-focused Machine Learning Engineer to build the data-creation systems that transform egocentric, robot, and sensor footage into training data for robotics and world-model teams.

You will apply computer vision techniques, SLAM, and 3D reconstruction to scale, tune vision models, and deploy end-to-end pipelines, collaborating with frontier labs. The role requires onsite work at SF HQ and a hands-on, data-driven mindset.

Qualifications

• 3+ years building production perception or CV systems for robotics, AR/VR devices, autonomous vehicles, or similar.
• Hands-on experience with SLAM, visual-inertial odometry, multi-view geometry, or 3D reconstruction.
• Strong Python skills and fluency with PyTorch; C++ is a plus.
• Experience training, fine-tuning, or deploying modern deep learning models for vision.
• Comfortable owning a problem from the customer conversation to a deployed pipeline.
• Excited about Physical AI and the data that will power it.
• In person at our SF HQ

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

Skills

Python

PyTorch

C++

SLAM

3D Reconstruction

Robotics

Vision systems

Job description

Sieve in San Francisco is seeking a perception-focused Machine Learning Engineer to build the data-creation systems that transform egocentric, robot, and sensor footage into training data for robotics and world-model teams.

You will apply computer vision techniques, SLAM, and 3D reconstruction to scale, tune vision models, and deploy end-to-end pipelines, collaborating with frontier labs. The role requires onsite work at SF HQ and a hands-on, data-driven mindset.