Data Annotator (HD Maps)

Job Title: Data Annotator/Map Annotator Location: Sunnyvale, CA (Onsite) Contract: 06+ months Top 3 Responsibilities: HD Map Creation & Layering: Constructing, annotating, and labeling static map layers, road features, intersections, and traffic landmarks from 3D LiDAR and 2D sensor data with centimeter-level precision. Validation & Operational Quality: Refining auto-generated maps, conducting rigorous QA reviews to fix algorithmic edge cases, and adhering to strict production instructions and KPIs. Cross-Functional & Metadata Integration: Tagging map elements with key semantic attributes (speed limits, lane types, restrictions) and collaborating with engineering teams to improve auto-mapping tools and guidelines. Description: We are looking for a highly skilled HD Map Data Annotator to join our AV Labs. In this role, you will be at the forefront of AV development, transforming raw sensor data into the foundational, high-fidelity maps that our self-driving algorithms rely on to navigate safely. You will focus primarily on static map generation and HD map labeling, handling complex tasks ranging from tracing drivable boundaries in point clouds to defining complex intersection topologies and traffic logic. The ideal candidate is a detail-oriented spatial thinker who understands that the safety and routing logic of autonomous systems start with the absolute precision of their underlying maps. Responsibilities: ● Static Map Generation: Annotate and construct foundational static map layers using 3D visual data (LiDAR/Point Cloud) and 2D high-resolution aerial or vehicle camera imagery. ● HD Map Labeling: Precisely label and classify static road features, including lane boundaries, centerlines, road edges, crosswalks, stop lines, and drivable surface areas. ● Topological Mapping: Build and verify complex intersection topologies, linking incoming/outgoing lane segments and defining vehicle trajectories for turn logic. ● Semantic Attribution: Tag map elements with critical metadata, such as speed limits, turn restrictions, vehicle class restrictions, and lane types (e.g., HOV, bike lanes). ● Traffic Landmark Association: Identify traffic lights and road signs, accurately associating them with their corresponding drivable lanes to ensure correct right-of-way logic. ● Auto-Map Refinement: Validate, correct, and refine auto-generated static maps, fixing algorithmic edge cases and ensuring centimeter-level precision. ● Quality Assurance: Conduct rigorous reviews of annotated map data to ensure topological accuracy, logical consistency, and "pixel-perfect" quality. ● Cross-functional Collaboration: Work closely with mapping and localization engineers to refine labeling guidelines, report sensor alignment issues, and improve auto-mapping model performance. ● Operational Excellence: Strictly follow complex project instructions, meet established deadlines, and achieve production KPIs without compromising on quality. Requirements ● Bachelor’s degree; a background in GIS, Geography, Urban Planning, or possess 3+years of relevant data annotation experience. ● Proven experience in data annotation specifically within the Autonomous Driving sector, with a strong emphasis on HD mapping or static environment labeling. ● Hands-on experience working with 3D/2D annotation tools, specifically navigating and manipulating LiDAR point clouds and orthophotos. ● Exceptional spatial awareness and the ability to understand complex road network structures, traffic rules, and lane connections. ● Strong knowledge of computer basics, data management techniques, and data analysis platforms. ● A proven track record of finding subtle anomalies (e.g., misaligned point clouds, conflicting lane logic) and following specific guidelines without subjective interpretation. ● Mental agility and the ability to pivot quickly between different geographic locations, mapping rulesets, and project types. ● Comfortable working on-site 5 days a week.