Data Annotator

Job Title: Data Annotation Specialist – Infotainment Logs Location: Remote Pay Range: $40–$50/hr (W2) Overview We are seeking a highly detail-oriented contractor to support the analysis and labeling of infotainment system logs. This role focuses on reviewing raw device logs, tagging relevant events, and generating high-quality annotated datasets used in model development, engineering diagnostics, and analytics workflows. Candidates must be comfortable working independently and navigating large, unstructured technical log files. Key Responsibilities • Examine infotainment system logs to identify important events, behavioral patterns, and system states. • Apply structured tags, metadata, and classifications based on established annotation rules and taxonomies. • Detect and categorize issues such as system warnings, connectivity drops, performance slowdowns, playback irregularities, and navigation-related faults. • Capture recurring behaviors, anomalies, and edge cases to aid engineering, QA, and ML training teams. • Deliver consistent, accurate labeling across all assigned tasks while meeting productivity expectations. • Provide input to refine annotation guidelines, workflows, and decision logic as needed. • Manage your own task queue and operate efficiently in a deadline-driven, independent work environment. Required Qualifications • Previous hands-on experience with data annotation, labeling, or training-data quality review—preferably involving system or technical log datasets. • Strong understanding of CAN protocol, with the ability to interpret automotive communication signals. • Experience with additional communication protocols such as I2C and SPI is highly beneficial. • Background working with infotainment logs, embedded/mobile system logs, or Linux/Android logging environments (e.g., logcat, system traces, connectivity logs). • Ability to navigate and analyze large volumes of raw, unstructured data. • Excellent attention to detail and strong pattern-recognition capabilities. • Clear written communication skills for documenting findings, summaries, and anomalies. • Familiarity with annotation tools, labeling platforms, or internal data-processing systems. • Experience collaborating with AI/ML, data engineering, or model development teams is a strong plus.