GeoPhy is a technology company in the real estate space. We provide property valuations engineered for the modern world, giving property lenders and investors fast, consistent and reliable access to information. Our technology allows our customers to understand value and its drivers by using both traditional and unconventional sources, using machine learning to create the most accurate valuations in the market.
GeoPhy’s multidisciplinary teams consist of data scientists, engineers, statisticians and economists, using data science and supervised machine learning to optimize the unprecedented volume and variety of data now available in the real estate sector.
We are looking for an experienced Data and Machine Learning Engineer to join our Data Science team and work on the development of cutting edge Machine Learning solutions for automated property valuations, asset recommendations and market forecasting.
You will work alongside Data Scientists on model development and join forces with data and software engineers to embed those models in production-ready Machine Learning pipelines. You will orchestrate ML production loads in AWS and work with our infrastructure team on our CD4ML efforts.
You’ll actively participate in the development of our Data Science computing platform and help us move towards a level 3 MLOps maturity level.
You’ll join the stellar Geophy Data Science and Analytics hub, where you’ll be able to do all of the above while having a lot of fun with colleagues from all over the world, and all the room you need to learn and grow as a world class Machine Learning Engineer.
The impact you will have
- Building machine learning pipelines to deliver predictions in production, at scale.
- Working on the development of the Geophy Data Science computing platform in AWS, our CD4ML tools and model monitoring mechanisms.
- Contribute to decisions about our technology stack, particularly as it relates to end-to-end ML model and data flow and automation.
- Developing proof-of-concept ML models to solve problems for a variety of data and domains, including entity resolution and linkage, deep learning for similarity learning, market time series forecasting.
- Being a team player and constantly coordinating with the other disciplines to deliver excellent products.
- Contributing to the Data Science Hub activities, supporting best practices, knowledge sharing and cross-functional initiatives.
What we’re looking for
- Creative and intellectually curious people with at least 5 years hands-on experience in machine learning engineering, or 5 years experience in data engineering and a strong attitude for machine learning.
- Rigorous engineers, which value building at scale and delivering at quality, and think of ML integration in software in terms of ML pipelines.
- Distributed computing enthusiasts, with at least 2 years of experience with Spark and the Hadoop ecosystem, along with other big data technologies.
- MLOPs fanatics, with proven experience in building CI/CD pipelines for machine learning models
- Python developers, programmers, with excellent knowledge of SQL.
- Generous, flexible team players.
- Amazing communicators who can convey the importance of their work to laypersons as well as peers.
- Full working proficiency in English.
Bonus points for
- Hands on experience with orchestrating machine learning and big data services in AWS (Step Functions, Sagemaker, EMR, S3, Amazon Aurora, Amazon Athena).
- Experience with orchestrating production workflows in Apache Airflow.
- Knowledge of Scala.
What we’re offering
- You will have the opportunity to accelerate our rapidly growing organization.
- We’re a lean team, so your impact will be felt immediately.
- Agile working environment with flexible working hours and location, career advancement, and competitive compensation package.
- GeoPhy is a family and pet friendly company.
- We arrange social activities to help our employees and families become familiar with each other and our culture.
- Diverse, unique colleagues from every corner of the world.
If you’re convinced you are the right fit and you can’t wait to join our team, we look forward to hearing from you!