LiDAR Labeling Operations

Hiring for MNC!!!
Job title : LiDAR Labeling Operations
Location : Remote
Experience- 0-2 years of experience (immediate joiner)
Contract- 12 months
CTC - 15k to 20k

Job Description
Multi-Sensor LiDAR Labeling Operations – Policy & Quality Expert
About the Role
We are seeking a highly detail-oriented and technically strong Multi-Sensor LiDAR Labeling Operations Policy & Quality Expert to lead labeling policy development, quality governance, and operational excellence across autonomous vehicle (AV) data annotation programs. This role sits at the intersection of perception systems, annotation operations, quality assurance, and scalable process design.
The ideal candidate has deep experience with LiDAR, camera, radar, and sensor-fusion annotation workflows, strong understanding of AV perception use cases, and a proven ability to define annotation standards that improve model performance and operational scalability.
You will partner closely with perception engineering, ML teams, program managers, QA leads, tooling teams, and external annotation vendors to ensure high-quality labeled datasets that support production-grade autonomous driving systems.

Key Responsibilities
Policy & Annotation Standards
Develop, maintain, and evolve annotation policies for:
3D LiDAR object labeling
Multi-sensor fusion workflows
Camera-LiDAR alignment tasks
Radar-assisted labeling
Semantic segmentation and tracking
Temporal consistency and trajectory annotation
Define clear taxonomy, ontology, edge-case handling, and escalation guidelines.
Translate perception model requirements into operational annotation specifications.
Create decision trees, annotation playbooks, SOPs, and reviewer guidelines.
Standardize annotation behavior across internal and external labeling teams.

Quality Management & Governance
Define quality metrics, acceptance criteria, and operational KPIs.
Design scalable QA frameworks including:
Golden tasks
Inter-annotator agreement
Reviewer calibration
Root-cause analysis
Error taxonomy
Conduct audits to identify systematic quality gaps and drive corrective actions.
Partner with ML/perception teams to measure annotation impact on model performance.
Lead continuous improvement initiatives to improve consistency, accuracy, and throughput.

Operational Excellence
Collaborate with labeling vendors and BPO partners to operationalize annotation policies globally.
Support workforce onboarding, certification, and calibration programs.
Analyze annotation productivity, ambiguity trends, and policy gaps.
Drive process automation opportunities with tooling and workflow teams.
Support large-scale dataset launches and quality readiness reviews.

If interested please share resume on [contact shared on WhatsApp]