What are the responsibilities and job description for the Staff Software Engineer - Map AI Platform position at Hivemapper?
Hivemapper is a decentralized global map data network built by 10s of thousands of people. High-res sensors feed sensor fusion and ML models at the edge, and data is automatically uploaded in near realtime. Enterprise tech, mapping, auto, robotaxis, rideshares, and real estate represent just a few of the customers consuming data today.
APIs allow anyone to consume high-res street-level imagery and precisely extracted Map Features (speed signs, turn restrictions, etc.). New data products for HD mapping, AI fleet management, construction understanding, and more are continuing to grow or launch throughout the year.
Map AI Platform
Every day, we process data from millions of KM from 10s of thousands of high resolution sensors deployed around the world. Different Sensor Fusion, ML, AI, 3D Reconstruction processes are performed at the edge and in our processing clusters, and the Map AI Platform orchestrates the efforts of a combination of AI and 10s of thousands of human taskers.
The Map AI Platform is the core data engine that powers our data customers and consumer products and user-facing AI technology. These complex systems control and learn patterns about this rich data all over the world and enable us to to continuously evolve semantic extraction, QA at scale, and training data generation. For example, we’ve recently been using the system to generate semantic labels for CV embeddings that enables very fast VLLM model fine-tuning loops.
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.
\n- 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
- 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
- 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
- Medical, dental and vision benefits plus FSA
- Family leave
- 401(k) program
- Unlimited Flex PTO
- Commuter benefits
- Paid lunch
