Python Engineer — ML Tooling & Annotation Platform

Role overview

Build and own the software that turns aerial imagery into reliable machine learning datasets. The annotation and dataset platform supports labeling, quality review, model-assisted pre-labeling, dataset versioning, and the pipelines that feed training; your work will help ML engineers and annotation teams use these tools in their daily workflows.

Responsibilities

- Develop the annotation platform, including task routing, consensus review, and pre-labeling that incorporates YOLO model inference. - Manage dataset infrastructure, covering versioning, class taxonomies, stratified splits, and traceability from raw imagery to trained model. - Make training workflows reproducible through experiment tracking and configuration management. - Build tools for submitting GPU jobs to internal clusters. - Deliver maintainable, tested Python services and command-line tools for platform users. - Assess whether tools meet team needs and refine or remove those that do not.

Requirements

- At least four years of production Python experience with services, APIs, and data pipelines. - Experience supporting machine learning workflows, such as annotation systems, dataset management, or training infrastructure. - A practical approach to building and maintaining tools around users’ needs.