Role Overview
A robotics dataset is fundamentally different than static 2D imagery. Every sample carries time-dependent movement, occlusions, state transitions, and interaction cycles. Quality issues propagate quickly if not caught early—one contributor misunderstanding a task can cause hundreds of unusable sequences.
This role designs the workflows that avoid that outcome.
You will own contributor scoring, inspection percentages, AutoQA thresholds, and acceptance logic—effectively designing how robotics data goes from raw → labeled → trusted → production-ready.
What You Will Own
Workflow Engineering
- Define contributor onboarding workflows for robotics projects.
- Build stage-gated review levels (100% review → 90% → 70% → floor threshold).
- Encode feedback loops so contributors improve and move faster over time.
Quality Management
- Identify failure modes across robotics use cases (hand occlusion, tracking drift, mis-bounds, missing state changes, etc.).
- Translate failure cases into rules, triggers, and annotation quality checks.
- Use automated validation (LLM or heuristic) to minimize unnecessary human review.
Review Load Optimization
- Design cost-vs-confidence strategies for review decisions.
- Track time-to-acceptance, rework rate, slack time, and rejection patterns.
- Reduce QA overhead as confidence increases.
Contributor Confidence Systems
- Build scoring profiles using:
- past approval rate
- rework volume
- escalation frequency
- time compliance
- Use scoring to automatically set review percentages.
What You Bring
- Experience working with robotics or real-world perception data workflows.
- Ability to identify data consistency issues and convert them into scalable rules.
- Understanding of large-scale review operations (internal or workforce-based).
- Experience with measurement frameworks (KPIs for labeling quality).
- Strong analytical skills with cost-aware decision-making.
Why This Job Exists
Every robotics project scales along three curves:
- Data volume
- Cost per sample
- Reliability requirements
Without automated workflow logic, cost per labeled sequence grows linearly or worse.
Your work makes it possible for:
- contributors to progress faster,
- QA teams to focus only where needed, and
- robotics orgs to iterate models more quickly.
You directly impact the throughput and viability of Labelbox’s robotics business.
Alignerr Services at Labelbox
As part of the Alignerr Services team, you'll lead implementation of customer projects and manage our elite network of AI experts who deliver high-quality human feedback crucial for AI advancement. Your team will oversee 250,000+ monthly hours of specialized work across RLHF, complex reasoning, and multimodal AI projects, resulting in quality improvements for Frontier AI Labs. You'll leverage our AI-powered talent acquisition system and exclusive access to 16M+ specialized professionals to rapidly build and deploy expert teams that help customers, which include the majority of leading AI labs and AI disruptors, achieve breakthrough AI capabilities through precisely aligned human data—directly contributing to the critical human element in advancing artificial intelligence.
