SimpleFinance is reimagining the home financing experience. We are removing friction throughout the process by applying machine learning and AI to streamline processing and more accurately underwrite risk. From deep analysis of property imagery, we are extracting assessments of condition to assign home values while also empowering customers with more advance tools to identify their next home. Together our team will drive the time to get a home loan from nearly 50 days down to fewer than 10.
We are looking for ML Engineer for building of our machine learning engine and ecosystem around it. This includes prototyping of new ML based models, analysis and collection of suitable data as well as transferring of the research to production and close cooperation with team on various levels of abstraction (product, business, infra & backed).
Current ML work is focused on integrating and cleaning of big data from our external sources as well as on modelling part. Our ensembled models are built upon imagery and structured data with special focus on confidence around our predictions.
Next we are going to expand our ML pipelines and scale our geographic data models used on California to the whole USA.
Apart from those challenges, we have plenty of exciting research task ahead of us. For example we plan to extend our computer vision modelling usage. Specifically to solve problems like identifying the property interior quality or identifying whether there is a view from the house to the ocean and much more.
- Analyze big structured and unstructured data
- Transfer the current research on field of ML into the production environment
- Design and build ML based pipelines (data, models, integration to production)
- Develop scalable machine learning models leveraging image, natural language and structured data domains
- Degree in Computer Science or a related quantitative field with relevant experience
- Experience with building machine learning models and defining prediction tasks
- Software development skills (Python is preferred)
- Experience with AWS infrastructure a plus
- Experience with the early-stage projects a plus
- Experience with deploying machine learning models to production a plus