In this role, you will analyze large-scale 2D/3D annotation datasets to identify data gaps,
quality issues, and operational inefficiencies, and build dashboards and metrics that
monitor annotation throughput, quality, cost, and vendor performance. You will partner
closely with Annotation Operations, Perception, and Engineering teams to ensure data
readiness for model training and evaluation.
The ideal candidate is data-driven, detail-oriented, and execution-focused, with a strong
understanding of annotation workflows and a passion for improving data quality and
efficiency at scale. This role plays a critical part in enabling informed decision-making,
continuous process improvement, and scalable annotation operations across internal
teams and external vendors

Data Analysis, Insights & Dashboards

• Analyze large-scale 2D/3D annotation datasets to identify data gaps, quality

issues, coverage gaps, and inefficiencies impacting Perception and ML training.

• Design, build, and maintain dashboards and reports to monitor:

Annotation Operations & Quality

• Assess level of effort for annotation projects and support end-to-end execution,

including in-house vs. vendor decisions.

• Collaborate with stakeholders to gather labeling requirements and define,

maintain, and evolve labeling policies.

• Define and track annotation quality, productivity, and certification metrics;

continuously refine benchmarks.

• Conduct QA/QC analysis on annotated data, identify systemic issues, and

provide structured feedback to annotators and vendors.

• Implement and measure labeling efficiency improvements, using data to validate

impact.

Process Improvement & Automation

• Identify opportunities to make data delivery and annotation workflows faster,

more accurate, and scalable.

• Build lightweight automation (scripts, queries, data pipelines) to reduce manual

reporting and operational overhead.

Cross-Functional & Vendor Collaboration

• Work closely with Annotation Ops, Perception, and Engineering teams to ensure

consistent process implementation.

• Support vendor management by analyzing performance, cost, and quality metrics

across multiple annotation partners.

• Prepare technical and operational reports to support planning, execution, and

decision-making.

• Coordinate across teams and time zones to ensure alignment and timely delivery.

Required

• BS degree in a technical or related field with 2+ years of relevant experience (or

5+ years equivalent industry experience).

• 2+ years supporting data annotation, ML data, or labeling-related projects.
• Strong understanding of 2D/3D data annotation workflows for ML and Perception

use cases.

• Hands-on experience with data analysis, metrics tracking, and dashboarding.
• Working knowledge of Python, SQL, databases, and/or data visualization tools.
• Experience analyzing LiDAR point clouds, video, and image annotation data.
• Ability to manage multiple projects, prioritize effectively, and deliver under tight

timelines.

Nice to Have

• Experience mentoring or guiding junior team members or offshore teams.
• Familiarity with annotation QA frameworks and error taxonomy design.
• Experience building or improving operational analytics for efficiency, cost, or

quality.

• Comfort working in a fast-paced, cross-functional, and collaborative environment.