Sieve
Roboticist, Physical AI
San Francisco · Mid
Sponsorship not specifiedDetected 14 hours ago
PythonC++SwiftLinuxSolidWorksPCB DesignAltiumKiCadRoboticsSensorsAR/VRCommunication
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odds of building a lasting career here
34Risky
Cap-exempt (no lottery)0
Sponsors this role70
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70
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Files H-1B transfers
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About the role
- Most of your week will be spent with real equipment: wiring and rewiring, bringing up new sensors, chasing calibration drift, and fixing whatever stopped recording overnight.
- We want someone who has run systems in real deployments and brings discipline to the work.
- When a rig works once, you want to know why, and you want it to work the same way at every site.
Responsibilities
- Capture rigs: Design and bring up the hardware we record with: multi-camera arrays, head- and wrist-mounted egocentric cameras, depth/IMU/force sensor packages, and teleoperation stations such as leader-follower arms.
- Calibration and time sync: Own camera intrinsics and extrinsics, hardware triggering, and clock alignment across cameras, IMUs, and encoders. If the streams don't line up, the dataset isn't usable.
- Field deployments: Set up and operate systems at partner sites. Build them to survive daily use, to be run by operators without robotics backgrounds, and to be repaired quickly on site.
- Robot and capture software: Write and maintain drivers, ROS/ROS2 integration, recording and logging, and QA checks that run at capture time and hand data straight to Sieve's pipelines.
- Repeatable builds: Produce BOMs, assembly docs, validation plans, and SOPs so we can stand up the same setup at the next ten sites without you there.
- Design and bring up the hardware we record with: multi-camera arrays, head- and wrist-mounted egocentric cameras, depth/IMU/force sensor packages, and teleoperation stations such as leader-follower arms.
- Own camera intrinsics and extrinsics, hardware triggering, and clock alignment across cameras, IMUs, and encoders.
Requirements
- 3+ years of experience building robotic, mechatronic, or controls systems (background in robotics, EE, ME, or similar)
- Experience as an early hire at a startup
Nice to have
- Systems you've deployed beyond the lab (in a factory, warehouse, field site, or customer site), plus stories about what failed and what you changed
Benefits
- 401(k) and full health insurance
Company info
- Sieve is a multi-modal lab curating the world's highest-quality training datasets - spanning video, audio, images, text, and 3D. We combine exabyte-scale data infrastructure and novel multimodal understanding techniques that push the frontier of foundation models. Video alone makes up 80% of internet traffic, and across modalities, data has become the enabling medium powering creativity, communication, gaming, AR/VR, and robotics. Sieve exists to solve the biggest bottleneck in the growth of these applications: high-quality training data.
- We partner with top AI labs and did $XXM last quarter alone, as a team of ~30 people. We also raised our Series A from Tier 1 firms such as Matrix Partners https://matrix.vc/, Swift Ventures https://www.swift.vc/, Y Combinator https://www.ycombinator.com/, and AI Grant https://aigrant.com/.
- Sieve is a multi-modal lab curating the world's highest-quality training datasets - spanning video, audio, images, text, and 3D.
- We combine exabyte-scale data infrastructure and novel multimodal understanding techniques that push the frontier of foundation models.
- Video alone makes up 80% of internet traffic, and across modalities, data has become the enabling medium powering creativity, communication, gaming, AR/VR, and robotics.
- Sieve exists to solve the biggest bottleneck in the growth of these applications: high-quality training data.
- We partner with top AI labs and did $XXM last quarter alone, as a team of ~30 people.
- We also raised our Series A from Tier 1 firms such as Matrix Partners https://matrix.vc/, Swift Ventures https://www.swift.vc/, Y Combinator https://www.ycombinator.com/, and AI Grant https://aigrant.com/.
- Sieve exists to solve the biggest bottleneck in the growth of these applications:
- high-quality training data.
This listing is sourced directly from Sieve's careers page and normalized into a canonical job model.