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Agentic Data Understanding

San Francisco, CA💼 Full-time🗓 2026-06-17 → 2026-07-30

Core

Design and build AI-driven systems to automatically generate high-quality annotations at scale for autonomous construction robots, transforming raw sensor data into structured, semantically rich data.

Role type

Senior IC Agentic Data Understanding Engineer

Builds

Auto-labelers, orchestration pipelines, quality harnesses, and agentic workflows for robot autonomy

Domain

Robotics, Autonomous Vehicles, Construction Technology

Deliverable

production ML models

Required skills

ML engineering, data engineering, applied AI, Python, complex pipeline development, ML model inference at scale, annotation modalities (2D bounding boxes, 3D cuboids, semantic segmentation, event/context labels), quality/cost tradeoff analysis, metric instrumentation, cross-functional collaboration

Preferred skills

Model fine-tuning, agentic or LLM-orchestrated pipelines, VLMs for zero-shot/few-shot annotation, robotics data formats (LiDAR, cameras, IMU), annotation platforms, ontology/taxonomy design

Technologies

Python, VLMs, LiDAR, cameras, IMU

Responsibilities

Design hybrid cascading auto-labeling pipelines; develop annotation harnesses for quality/cost assessment; productionize annotation workflows; build and maintain the Annotation Orchestrator; implement scheduling logic for parallel workflows; build agentic annotation workflows for self-diagnosis and human-in-the-loop review; develop tooling for annotation versioning; define and instrument metrics for quality/cost optimization

Seniority

Senior, hands-on IC

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