Machine Learning & Data

Our team combines a robust data platform with cutting edge technology from various cross functional industry expertise to fuel our growth strategy, market launches and deployment of hundreds of millions of dollars in capital to reshape the housing market. We innovate and make a tangible business impact by working on applied problems to solve a housing crisis that has increasingly plagued the country for the last 5 decades.

Hear from our team.

What's the most rewarding initiative you have been part of at Homebound?

Larry Ogrodnek, Software Engineer

What’s been the most interesting aspect of working on data intensive applications?

Kimiko Kano, Software Engineer

What was your onboarding experience like at Homebound?

Nikhil Bhargava, Data Scientist

Meet the team.

Learn more.

More about Homebound

‍

From the Technology Blog

Careers

Check out our open roles

View all openings

Team Size & Roles

Head of Data/Machine Learning

1 Employee

ML Engineers‍

3 Employees

Data Scientists

2 Employees

Software Engineers (Data, Backend, Full Stack)

3 Employees

Collaboration Practice

We believe that machine learning is a team sport so we value collaboration. Our best practices include the following:

Written Design Docs/RFCs for larger initiatives
Daily standups (expect “No-meeting Fridays”)
Bi-weekly grooming & planning
Sprint retrospective and demos (agile methodologies)
Pair programming
Peer level 1:1s
Quarterly voluntary in-person collaboration (usually somewhere fun and new each time!)

Tools and Tech We Use

We like to leverage tools and technologies that have been battle tested and can be deployed around simple and scalable AWS architectures. Here’s a preview:

‍

Frontend: TypeScript

Backend & ML: Python

AWS

Sagemaker
Athena
S3
ECR/ECS

Orchestration

Airflow

Version control

Github

Machine Learning

Sklearn
Xgboost
MLflow
Shapley
Pytorch/Tensorflow (coming soon!)
Hugging Face (coming soon!)

Other tools

Docker
CircleCI
Looker