Drive the architecture, design, implementation, and evaluation of AI systems and data platforms while mentoring teams and contributing to technical strategies.
Hivemapper is a decentralized global map data network built by 10s of thousands of mapping devices. High-res sensors like RGB, Stereo Depth, GNSS, IMU, etc. feed sensor fusion and ML models at the edge. Data is automatically uploaded in near realtime over LTE or WiFi. Enterprise tech, mapping, auto, robotaxis, rideshare, and entertainment represent some of the customers consuming data today.
APIs allow anyone to consume precisely extracted Map Features, HD map data, high-res street-level imagery, construction, and driving events for AV simulation. Tech-savvy customers develop and deploy software directly to our dashcams to get realtime data for things like change detection or visual semantic data mining. AI Fleet management tools drive value to large fleets of vehicles.
Map AI Platform
Every day, we process data from millions of KM from 10s of thousands of high resolution sensors deployed around the world. A symphony of different Sensor Fusion, ML, AI, 3D Reconstruction processes are performed at the edge and in our processing clusters, for which the Map AI Platform orchestrates.
The Map AI Platform is the core data engine that powers our data customers, consumer products, and user-facing AI technology. These complex systems control and learn patterns about map data all over the world and enable us to to continuously evolve map data intelligence, semantic extraction, QA at scale. For example, we’ve recently been using the system to learn hyperlocalized road network patterns to automatically QA and correct noise from map conflation.
We strongly believe in engineering design principles around abstraction and programmability that allow us to move quickly with minimal manual interventions. Our work is fast-paced, collaborative, and data-driven.
Responsibilities
- Drive architecture, design, implementation, and eval of our core ai systems and data platform
- Partner across company to ensure our systems are adaptable to emerging opportunities
- Help plan technical roadmaps and contribute to higher level technical strategy
Requirements
- Experience building production critical systems used by >=10s of thousands of users
- Deep backend experience with large scale data platforms, DBs, ETL, distributed systems, etc.
- Strong analytical skills in a relevant field like ML, math, statistics, quantitative economics, etc.
- Track record of leading and mentoring teams in successful projects
Nice to Have
- Experience generating, augmenting, and managing large amounts of ML training data
- Experience integrating or training/fine-tuning ML CV vision models, VLLM models, etc.
- Familiarity with geospatial data, HD mapping, sensors fusion, ADAS or AV, etc.
- Experience scaling products or systems at hyper-growth startups
What we offer
- Medical, dental and vision benefits plus FSA
- Family leave
- 401(k) program
- Unlimited Flex PTO
- Commuter benefits
- Paid lunch
Hivemapper San Francisco, California, USA Office
San Francisco, CA, United States
Similar Jobs
Artificial Intelligence • Cloud • Computer Vision • Hardware • Internet of Things • Software
Own and execute the multi-year telematics hardware platform roadmap end-to-end. Drive commercial outcomes for gateways, sensors, cabling and accessories through field validation, launch, lifecycle management, and cross-functional alignment. Engage customers and sales on strategic deals, use market and fleet data to prioritize, and mentor junior PMs while ensuring hardware strategy supports revenue, margin, and company growth.
Top Skills:
Can BusCloudEdge AiFccIotJ1939Obd-IiPtcrbSensorsTelematicsVehicle GatewaysWireless
.jpg)
Fintech • Insurance • Payments • Social Impact • Financial Services
The role involves sourcing new business for 1031 QI services, building client relationships, and facilitating tax-deferred exchanges while working independently and leveraging industry knowledge for client satisfaction.
Manufacturing
Perform manual production tasks including assembling boxes, packaging, taping, labeling, sorting, and quality inspections. Record weights and production counts, follow standard operating procedures, and ensure correct packaging for fragile items. Frequent walking/standing and lifting up to 50 lbs required.
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
