Hivemapper

Hivemapper

Technical Product Manager

San Francisco, CA, United States

Sponsorship not specifiedDetected 1734 days ago
SQLMachine LearningData VisualizationComputer VisionProduct ManagementProduct StrategyBusiness DevelopmentSupply ChainLogisticsRoboticsSensorsGIS

About the role

  • Hivemapper is a decentralized map built by people using their smartphone, dashcam, or drone.
  • It represents a fundamental shift in how maps are built.
  • Forward looking businesses use our Map API.

Responsibilities

  • Partner with internal and external stakeholders to drive results and ensure high product quality
  • Develop new features and become an expert across street-level imagery, mapping, and blockchain.
  • Define and execute product roadmap and strategy, drive new business development, monitor and forecast product success
  • Furthermore, Hivemapper does not pay placement fees for candidates submitted by any agency other than its approved partners.
  • The Street-Level Imagery PM will work directly with our hardware partners on the R&D, manufacturing & supply chain, and global distribution of many thousands of sensor units in 2022.

Requirements

  • Product management or technical experience in mapping, IoT, or autonomy/robotics
  • Ability to thrive working in a fast paced agile environment
  • Experience overseeing an entire product development lifecycle
  • Experience with mass producing consumer sensors
  • Experience working at a startup
  • Experience with blockchain
  • Experience with mapping/GIS
  • Experience with ML and CV

Benefits

  • Medical, Dental and Vision Benefits
  • Commuter Benefits
  • We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Company info

  • Empathize with our contributors and customers alike

Equal opportunity

  • We are an equal opportunity employer and value diversity at our company.

This listing is sourced directly from Hivemapper's careers page and normalized into a canonical job model.