Mach9 is at the forefront of leveraging advanced machine learning and computer vision techniques to transform raw geospatial data into actionable insights, empowering civil engineers to design, build, and maintain infrastructure worldwide. Our first product, Mach9 Digital Surveyor, helps surveyors automatically extract features from large-scale imagery and 3D datasets 96x faster than today's manual and labor-intensive drafting workflows, accelerating the development of cost-effective and sustainable transportation and utility infrastructure. Mach9 supports leading asset owners and engineering and construction organizations globally to solve the toughest engineering design, mission planning, and asset management problems.

Mach9 is backed by Quiet Capital, Y Combinator, Overmatch Ventures, Kyle Vogt (founder of Cruise), Amar Hanspal (former CEO of Autodesk), Scott Belsky (CPO of Adobe), Gokul Rajaram (former executive at DoorDash), and more.

We are seeking a Software Engineer to join our team and play a pivotal role in transforming large-scale geospatial datasets into structured and accessible formats. In this role, you will work with high-volume data sources, including laser scan point clouds, imagery, and other geospatial data formats, to ensure they are processed, stored, and made available for internal use in a consistent and efficient manner.

Responsibilities

• Convert third-party geospatial datasets into a standardized internal format.

• Develop and implement scalable workflows for processing large volumes of data.

• Create CI/CD pipelines to ensure consistency and correctness of data pipelines.

• Optimize the processing performance and query and storage efficiency of data pipelines.

• Work closely with customers and data provider partners to facilitate data integration (with occasional travel).

• Triage dataset processing errors, identify fixes and/or report issues to the customer success team.

• Be willing to puzzle hunt: be ready to work with data formats with little documentation.

Requirements

• Strong software development, problem solving and debugging skills with experience in Python and C++.

• Knowledge of distributed systems and parallel computing.

• Bachelor’s degree in Computer Science, Engineering or equivalent experience

• Strong communication and collaboration skills.

• Experience working with point cloud and imagery data pipelines.

Preferred qualifications

• Expertise in designing and managing data schemas and database systems for geospatial data (e.g., Postgres/PostGIS, AWS S3).

• Experience with large-scale data processing frameworks and cloud platforms (e.g. Spark).

• Understanding of geospatial data formats (e.g., LAS/COPC, GeoTIFF, Shapefiles) and tools (e.g., GDAL, PDAL).