Machine Learning Engineer
Role details
Job location
Tech stack
Job description
We are looking for a Machine Learning Engineer to take ownership of our geospatial data products.
In this role, you won't just train models or query data; you will architect the entire lifecycle of the data. From orchestrating complex pipelines on Kubernetes to rendering high-performance visualizations on Mapbox, you will build the engine that powers our real estate insights.
This is a heavy "Builder" role. We need someone who is as comfortable debugging an Airflow DAG as they are calculating spatial statistics. The Stack
You will have full autonomy over a modern, high-performance stack:
- Data Storage: Postgres (PostGIS) for spatial transactions, ClickHouse for massive-scale analytics.
- Code: Python (Production-grade)., * End-to-End Pipelines: Design and deploy automated pipelines (ETL) using Airflow to ingest diverse datasets (Real Estate transactions, listings, geo-data).
- Geospatial Analytics: Compute advanced spatial metrics (e.g., pricing honeycombs, average prices per neighborhood) using PostGIS and Python.
- Infrastructure Management: Maintain and optimize the Kubernetes environment where your pipelines and models run.
- Visualization Engineering: Transform your analytical outputs into interactive map layers (Vector Tiles) that integrate seamlessly with Mapbox on our frontend.
Who You Are
- You are "Full Stack": You reject the idea that Data Scientists shouldn't touch infrastructure. You know that to deliver value, you need to own the deployment.
- You love Maps: You have an intuition for spatial data-you understand projections, polygons, and how to visualize density effectively.
- You write clean code: You don't just write scripts; you write maintainable, modular Python code that can run reliably in production.
Requirements
- Experience: 3+ years in a Data Science or Data Engineering role with a focus on production systems.
- Engineering Chops: proficiency with Docker and Kubernetes is essential. You must be able to troubleshoot your own deployment environments.
- Database Fluency: Expert-level SQL, specifically with PostGIS or similar spatial extensions. Experience with ClickHouse is a strong plus.
- Tooling: Deep experience with Airflow for orchestration.
Ready to build something that truly scales?