Staff ML Engineer — Perception & 3D Vision (Onsite SF)

Sieve, Inc.; San Francisco (CA); In loco; USD 180.000 - 250.000; Tempo pieno

Vantaggi offerti da questo lavoro

Health insurance

Meals provided

Onsite SF HQ

Descrizione del lavoro

Sieve, Inc. in San Francisco is seeking a Perception-focused Machine Learning Engineer to build the data pipelines turning raw egocentric, robot, and sensor footage into labeled training data for robotics and world-model teams.

You will ship end-to-end perception systems, apply SLAM and 3D vision techniques, and collaborate with frontier labs to scale datasets across modalities. This role is onsite at our SF HQ.

Competenze

• 3+ years building production perception or computer vision 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
• Comfortable with multi-sensor data such as camera intrinsics and extrinsics, IMU, depth, and time synchronization
• Experience training, fine-tuning, or deploying modern deep learning models for vision
• Sharp intuition for evaluation, edge cases, and what makes data actually useful for training
• 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

Mansioni

• 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

Conoscenze

Perception systems

SLAM

Visual-inertial odometry

3D reconstruction

Python

PyTorch

C++

Multi-sensor data

Deep learning for vision

Data evaluation

End-to-end ownership

Physical AI

Strumenti

Python

PyTorch

C++

Descrizione del lavoro

Sieve, Inc. in San Francisco is seeking a Perception-focused Machine Learning Engineer to build the data pipelines turning raw egocentric, robot, and sensor footage into labeled training data for robotics and world-model teams.

You will ship end-to-end perception systems, apply SLAM and 3D vision techniques, and collaborate with frontier labs to scale datasets across modalities. This role is onsite at our SF HQ.