Work involves making cartographic edits in OpenStreetMap, annotating and classifying map imagery, validating and editing large volumes of map data (tens of thousands of items per week), and producing content for Mapbox navigation and mapping products. Requires decent English (A2+), ability to work from the office during probation and visit periodically, and attention to repetitive, high-volume tasks.

The role focuses on developing scalable data pipelines and backend services that aggregate and process global EV charging station data from charge point operators and aggregators. Responsibilities include designing data validation and quality systems, improving reliability and throughput of ingestion pipelines, building internal monitoring and tooling, supporting downstream teams, participating in on-call rotation, and working with product and engineering stakeholders. Strong production Rust experience and container-based AWS deployment experience are emphasized.

Join Mapbox's Roads team to own, improve, scale and build data processing pipelines used for road networks, navigation, and HD maps. Responsibilities include pipeline design/implementation, collecting and monitoring performance metrics, and contributing to security best practices. Required skills: at least one programming language (C++, Python, Scala, or Java), experience with AWS services (S3, EC2, IAM, EMR, Glue, Athena, Kinesis) or other cloud platforms, strong SQL knowledge, distributed computing, and experience with workflow tools (Airflow, Oozie, Luigi). Hybrid/remote work options are offered.

Join Mapbox's Roads team to own, improve, scale, and design data processing pipelines for road networks used in mapping and navigation. Role expects proficiency in at least one of C++, Python, Scala, or Java; experience with AWS services (S3, EC2, IAM, EMR, Glue, Athena, Kinesis) or other cloud platforms; strong SQL and distributed computing knowledge; and experience with workflow tools such as Airflow, Oozie, or Luigi. English fluency required.

Lead engineering work on highly trafficked recommendation systems for the routing cost engine, including designing/building ML and data pipelines, leveraging geospatial algorithms, partnering with data scientists, building automated QA and data exploration tools, mentoring engineers, and participating in an on-call rotation. Requires ~8+ years backend and ML experience and familiarity with Python, distributed processing (Hadoop, Spark, Airflow, Dask), cloud infrastructure (e.g., AWS), and reinforcement learning.