Machine Learning Engineer

RealAdvisor S.A.; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

RealAdvisor S.A. приглашает инженера по данным и ML для полного владения геопространственными продуктами, от ETL до визуализации на карте Mapbox. Роль предполагает работу с Airflow, Kubernetes и PostGIS в условиях удалённой и международной команды.

Требуется 3+ года опыта в DS/DE, умение писать чистый код на Python для продакшна и владение современными инструментами обработки данных. Работа полностью удалённо с гибким графиком.

Qualifications

• Опыт работы в DS/DE с владением продакшн‑системами не менее 3+ лет.
• Умение проектировать и поддерживать конвейеры данных, ETL/ELT.
• Опыт работы с геопространственными данными, PostGIS/Spatial SQL.

Responsibilities

• Оркестрация и эксплуатация: Airflow, Kubernetes, Docker.
• Хранение данных: Postgres (PostGIS) и ClickHouse для аналитики.
• Программирование: Python на продакшн‑уровне.
• Разработка и развёртывание ETL‑пайплайнов с Airflow.
• Геопространательная аналитика и визуализация слоёв на карте (Mapbox).
• Управление инфраструктурой Kubernetes и оптимизация рабочих сред.

Skills

Full-stack data

Geospatial intuition

Python production code

Data pipeline ownership

Airflow

Tools

Docker

Kubernetes

Airflow

PostGIS

ClickHouse

Mapbox

SQL

Job description

Описание:

RealAdvisor is one of the leading digital platforms in the European real estate ecosystem. Founded in Switzerland, we now support 5,000+ real estate agencies and attract 10+ million users per year across Europe. We are scaling fast across multiple markets with a clear mission: help real estate professionals grow through data, transparency and smart technology. At RealAdvisor, we value ownership, autonomy and impact. We are looking for a Machine Learning Engineer to take end-to-end ownership of our geospatial data products. This is not a model-tuning role. You will design, build, and operate the full data lifecycle behind our real-estate insights - from orchestrating complex pipelines on Kubernetes to delivering high-performance geospatial visualizations with Mapbox. This is a builder role. You should be as comfortable debugging an Airflow DAG as you are computing spatial statistics or optimizing analytical queries.

Задачи:

• Orchestration & Operations: Airflow, Kubernetes, Docker
• Data Storage: Postgres (PostGIS) for spatial workloads; ClickHouse for large-scale analytics
• Programming: Production-grade Python
• 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

Требования:

• Truly Full-Stack (Data): You don’t believe data scientists should stop at notebooks. You own infrastructure, deployment, and reliability because that’s how real value is delivered
• Strong Geospatial Intuition: You understand projections, polygons, spatial joins, and how to visualize density and patterns effectively
• Engineering Mindset: You write clean, modular, maintainable Python code designed for production - not one-off scripts
• Experience: 3+ years in a Data Science or Data Engineering role, with hands‑on ownership of production systems
• Infrastructure Proficiency: Solid experience with Docker and Kubernetes, including debugging and troubleshooting live environments
• Database Expertise: Advanced SQL, especially with PostGIS or similar spatial extensions. Experience with ClickHouse is a strong plus
• Orchestration Mastery: Deep hands‑on experience with Airflow for building and maintaining reliable data pipelines
• Fully remote role with flexible working hours. Close collaboration with leadership and go-to-market teams. International, ambitious, and collaborative team culture

Условия:

Fully remote role with flexible working hours. Close collaboration with leadership and go-to-market teams. International, ambitious, and collaborative team culture.