Data Labeling Specialist

Job Summary

The Data Labeling Specialist applies structural annotations and metadata to multi-sensor data streams using proprietary internal software tools. This specialist identifies computer vision data anomalies, documents edge-case ambiguities for machine learning teams, audits dataset quality metrics, and provides structured feedback to Autonomy developers to optimize data labeling throughput and user interface usability.

Key Roles & Operational Responsibilities

1. Multi-Sensor Data Annotation & Quality Auditing

• Stream Tagging: Label, annotate, and enrich raw data emerging from multiple drone sensor streams, applying metadata accurately to feed machine-learning algorithms.
• Guideline Enforcement: Apply detailed annotation rules consistently across diverse data batches to ensure all datasets are clean, uniform, and production-ready.
• Cadence Fulfillment: Generate and deliver validated, labeled datasets on a strict, regular schedule to keep pace with critical algorithm development timelines.

2. Edge-Case Identification & Engineering Escalation

• Anomaly Isolation: Examine visual data feeds to catch data anomalies, recurring visual ambiguities, and critical operational edge cases.
• Issue Documentation: Log and escalate systemic software bugs, tool friction points, or data quality degradation issues that threaten data ingestion throughput or accuracy.
• Autonomy Cross-Collaboration: Provide structured feedback directly to Autonomy engineering teams regarding the usability, efficiency, and quality control of internal labeling tools.

Foundational Capabilities & Prerequisites

Required Technical Profile & Experience

• Academic Foundation: Must hold a Bachelor’s degree in an Engineering field (or be a final-year student with all academic requirements completed and graduation pending).
• Data Processing Background: Proven experience reviewing, formatting, or labeling digital data sets, with a demonstrated ability to follow meticulous technical guidelines without deviation.
• Task Organization: Strong track record of tracking complex tasks or technical projects while maintaining organized, accurate logs and metadata records.
• Sustained Detail Focus: Exceptional attention to detail, with the mental stamina to maintain high precision during extended periods of methodical visual review.
• Communication Command: Excellent written and verbal communication tools in English to explain data trends or tool issues clearly to engineering partners.
• Legal Authorization: Must possess the verified legal right to work on-site in Rwanda.

What Zipline Offers

• Frontline AI Impact: Play a direct role in building the machine learning foundation for autonomous systems that deliver life-saving medical supplies worldwide.
• First-Principles Growth Environment: Work alongside world-class engineers in an environment that solves complex, real-world problems from first principles and rewards rapid innovation.
• Inclusive Tech Culture: Advance your career within a diverse corporate framework that welcomes unique perspectives and supports traditionally underrepresented professionals in technology.

Skills Required:

• Computer / Software / It / Data