Homebound’s mission is to make it possible for anyone, anywhere to build a home using leveraging technology, and we’re already delivering on that mission in places that need it most: communities impacted by natural disasters + communities with massive housing shortages. 

With technology behind every step of the process, Homebound delivers unprecedented homeowner experiences + a more efficient build process that will enable us to transform the single family home construction market, and build + rebuild communities along the way.

We are already helping hundreds of homeowners in California and Texas, and with over $70M in capital raised from Thrive, Fifth Wall, Google Ventures, Khosla and more, we are expanding faster than ever to help thousands more. Join us!

Role Overview:

Leveraging data throughout every step in the homebuilding process is critical to achieving Homebound’s mission. Homebound is looking for our first machine learning hire who is motivated about all parts of the ML lifecycle and excited to build and maintain our first set of ML data products. This is an exciting ground floor opportunity to tackle challenging ML problems with ample growth opportunities at a venture backed, growth stage company. 

From feature engineering to model explainability, from data lakes to MLOps, you get excited about the challenge of going from “zero to one” and from “one to N” on all things data/ML. 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 folks. If you have deep experience deploying ML products and are excited to build a new platform from scratch, then this opportunity is for you! 

#Li-Remote

What You Will Build:

• Robust home value prediction models that will be used to deploy capital across all of Homebound’s markets
• Propensity score models to ensure we are prioritizing focus on the right customers, at the right time
• Organizational Feature Engineering store to accelerate ML/DS projects across the organization
• MLOps platform and features to ensure we can easily train, deploy, monitor, and maintain a growing set of ML and data products
• Many more, including new ideas and features from you! 

Responsibilities:

• Establish and grow 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 and TensorFlow
• Experience working with AWS, ideally with SageMaker, Glue, and Athena
• Experience as a technical or team lead

We are focused on building a diverse and inclusive workforce. If you’re excited about this role, but do not meet 100% of the qualifications listed above, we encourage you to apply.

Homebound is an Equal Opportunity Employer and considers applicants for employment without regard to race, color, religion, sex, orientation, national origin, age, disability, genetics or any other basis forbidden under federal, state, or local law. Homebound considers all qualified applicants in accordance with the San Francisco Fair Chance Ordinance.

Please review our CCPA policies here.