Data Annotation Engineer Jobs in San Francisco, CA

We build storage and a high-throughput data engine over petabytes of video, lidar and high-frequency telemetry data to power frontier robotics and Physical AI labs

The Role We’re looking for a Robotics Data Infrastructure Engineer to own and build the data systems that power Verne

You'll work directly with researchers — and with the engineers who support them — to understand how they actually work, where managing data slows them down, and

Experience designing and building scalable data and annotation pipelines, as well as evaluation systems for AI model quality.

Our open-source engine, Daft, is the distributed data engine purpose-built for multimodal AI — already running 2 PB/day at Amazon,

Our platform indexes, curates, annotates, and evaluates data across the full AI lifecycle, from development through production.

About the Role As a Data Program Manager in the Human Data team you will partner with our research teams, operations and engineering

The Team High-quality data is the fuel for our work. The Annotations team produces high-quality data labels to support model development.

the post-training data for our large language models (LLMs), from SFT and RL data to synthetic and human-annotated data.

annotation, curation, and quality review Build and improve QA processes to ensure data output meets the standards required by frontier AI labs

Scope: Own data collection and creation programs from planning through delivery.

Our platform indexes, curates, annotates, and evaluates data across the full AI lifecycle, from development through production.

Ocular AI Ocular AI is the data annotation engine for Generative AI, Computer Vision, and Enterprise AI models.

As an ML Infra Engineer (Data Systems), you’ll build and operate the data infrastructure that powers large-scale robot learning.