Map Annotator#26-06316 San Francisco, CA Onsite Contract - W2 Starts 9/14/2026 Ends 3/13/2027 Job Description Map Annotator

Key Details:

Location:

Sunnyvale, CA

Duration:

6 months

Schedule:

Monday-Friday, 8:00 AM-5:00 PM PST

Hours:

40 hours/week; overtime as required

Work Arrangement:

Onsite

Compensation:

$40.00 - $43.00/hour

Employment Type:

W2 (not open to C2C, 1099, or visa sponsorship) Role Overview Our client is seeking a highly skilled HD Map Data Annotator to join their team. In this role, you will be at the forefront of autonomous vehicle development, transforming raw sensor data into the foundational, high-fidelity maps that 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 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. Qualifications Bachelor's degree in GIS, Geography, Urban Planning, or 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. Proven track record of identifying 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. Ability to work onsite 5 days per week in Sunnyvale, CA. Preferred Qualifications Experience collaborating directly with engineering teams to refine guidelines and resolve mapping edge cases. Familiarity with autonomous vehicle sensor suites and data processing workflows.