Senior Software Engineer (San Francisco, CA)

• 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.

Responsibilities

• Architecting, building and developing large-scale infrastructure, distribute systems and networks;

training other teams on these systems

• Researching and developing new technologies in large scale decentralized computer and web3

systems; integrating with core systems

• Applying expertise with data structures or algorithms in an academic setting to create core

abstractions for 100s of thousands of users and 100s of millions of square miles of data

• Working closely with operations, product development, and other engineering teams to deliver

data-intensive cross-functional platform solutions

• Building auditable and observable systems that can robustly handle billions of video frames each

day

• Helping to foster engineering excellence across backend development

Qualifications

• Master’s degree in Computer Science, Software Engineering, or a closely related field or foreign

equivalent

• 2 years (24 months) of experience with each of the following:
• Building scalable, fault-tolerant, and high-performance distributed systems; infrastructure

automation and optimization.

• Advanced data structures, indexing, partitioning, replication, horizontal scaling, and fault

tolerance.

• Translating business needs into technical solutions, mentoring engineering teams, and

fostering technical excellence.

• Implementing logging, monitoring, tracing, audit trails, and data compliance processes.
• Tools and technologies: Docker, Terraform, Apache Spark, Hadoop, PostgreSQL/PostGIS, Redis, Prometheus, Grafana, Git, AWS Lambda, AWS ECS, AWS Fargate, AWS EC2, AWS EMR, AWS Glue, AWS S3, and Node.js.
• Programming languages: Rust, Python, SQL/NoSQL, JavaScript, and TypeScript.

• -Experience may be gained concurrently and may have been gained pre-, during, or post-master's
• degree.