Homebound
Prior Listings
Sr. Machine Learning Engineer
Sr. Machine Learning Engineer
Role Overview:
Leveraging data throughout every step in the homebuilding process is critical to achieving Homebound’s mission. Homebound is looking for machine learning engineers who are motivated to create cutting edge pricing models that accurately predict the current and future value of homes. Our models are core to our land acquisition strategy and we are looking for talented teammates to take us to the next level!
You are equally comfortable writing detailed design documents, writing and deploying high-quality code and systems, working closely with teams across the company, and identifying, hiring, and partnering with other talented teammates. If you have deep experience building ML products and are excited to build innovative models and platforms from the ground up, then this opportunity is for you!
What You Will Build:
- Robust home value prediction models (AVMs) that will be used to accurately measure current and future home values and deploy hundreds of millions of dollars of capital across a growing number of markets.
- Large scale feature engineering across a variety of data types (tabular, geospatial, images, and text)
- Home Price Appreciation (HPA) models to accurately predict future home values across different levels of granularity.
- Lead Scoring & Propensity Models to identify the most attractive properties for Homebound to acquire and develop.
- Many more, including new ideas and features from you!
Responsibilities:
- Expand Homebound’s machine learning capabilities and tech stack.
- Identify, architect, and deploy high value ML opportunities across Homebound’s product suite
- Deploy high quality production code on a daily basis
- Design and build best-in-class data products, workflows, and standards through simple and scalable AWS architectures
- Understand the importance of organizational feature engineering and MLOps and incorporate these into the ML roadmap
- Help recruit and mentor a growing team of leading data/ML professionals
What You Have Done In Your Career:
- 5+ years of professional industry experience as a ML Engineer, Data Scientist, or Software Engineer with a focus on building production data/ML products
- Demonstrated success across the entire ML lifecycle including feature engineering, model development, model deployment, & model maintenance
- Deep experience with multiple modern ML frameworks like Scikit-learn, PyTorch, TensorFlow, and Hugging Face
- Experience working with AWS, ideally with SageMaker, Glue, Athena, ECS/Batch
- Experience as a technical or team lead