Bedrock Robotics

Agentic Data Understanding

San Francisco, CA

Sponsorship not specifiedDetected 35 days ago

Machine LearningData EngineeringLLMsRoboticsSensors

About the role

To do that, we need machines that deeply understand the built world - and that starts with data.
The Data Understanding Program is the backbone of how we annotate, search, and explore the robot data that powers our autonomy stack.
This role sits at the intersection of applied ML, data infrastructure, and robotics, and will directly shape how fast Bedrock can expand its operational domain.

Develop and maintain annotation harnesses that automatically assess quality and cost against golden/validation sets to enable continuous hill-climbing on label quality.
Build and maintain the Annotation Orchestrator that executes annotation job sequences, tracks progress, and manages integrations with external vendors.
Implement scheduling and prioritization logic for annotation jobs across multiple parallel workflows and data modalities (2D boxes, 3D cuboids, events, metrics, embeddings).
Own the annotation job configuration library - the registry of available annotators - and ensure new annotator technologies are onboarded in a scalable, secure way.
Develop tooling for annotation versioning and downstream propagation so that spec updates automatically trigger re-annotation of affected data.
Partner with the Data Infrastructure team to store annotations in queryable, version-controlled databases that support cross-domain semantic search and exploration.
Build reporting and dashboards to surface quality/cost trends across annotation workflows and inform decisions on when to invest in better auto-labeling vs. human annotation.
Experience building agentic or LLM-orchestrated pipelines (e.g., using VLMs for zero-shot or few-shot annotation).

8+ years of experience in ML engineering, data engineering, or applied AI - with meaningful time spent building production annotation or labeling systems.
Hands-on experience with one or more annotation modalities: 2D bounding boxes, 3D cuboids, semantic segmentation, event/context labels.
Ability to work cross-functionally with autonomy engineers, product managers, and human labeling teams.

Familiarity with robotics data formats and sensor modalities (LiDAR, cameras, IMU).
Experience with annotation platforms.
Background in robotics, autonomous vehicles, or construction technology.
Experience designing ontologies or taxonomies for structured data labeling.

Bonus: Hands on model fine tuning experience.
Productionize annotation workflows: backfilling historical data, triggering runs on new data programmatically, and tracking coverage across the fleet.
Build agentic annotation workflows that can reason about annotation quality gaps, self-diagnose failures, trigger human-in-the-loop review when confidence is low, and iterate toward coverage goals autonomously.

At Bedrock, we're moving AI out of the lab and into the real world.
Our team is composed of industry veterans who helped launch Waymo, scaled Segment to a $3.2B acquisition, and grew Uber Freight to $5B in revenue.
Today, we're deploying autonomous systems on heavy construction machinery across the country, accelerating project schedules of billion-dollar infrastructure projects and improving safety on job sites.
Backed by $350M in funding, we're working quickly to close the gap between America's surging demand for housing, data centers, manufacturing hubs, and the construction industry's growing labor shortage.
This is where algorithms meet steel-toed boots.
You'll collaborate with construction veterans and world-class engineers to solve physical-world problems that simulations can't touch.
If you're ready to apply cutting-edge technology to solve meaningful problems alongside a talented team-we'd love to have you join us.

This listing is sourced directly from Bedrock Robotics's careers page and normalized into a canonical job model.