Senior Research Engineer – Deep Learning

Key Skills

Java Programming, Python Programming, SQL, Deep Learning, PyTorch, TensorFlow, Docker, Dagger2

Job Description

Founded in 2014, Opendoor’s mission is to empower everyone with the freedom to move. We believe the traditional real estate process is broken and our goal is simple: build a digital, end-to-end customer experience that makes buying and selling a home simple, certain and fast. We have assembled a dedicated team with diverse backgrounds to support more than 100,000 homes bought and sold with us and the customers who have selected Opendoor as a trusted partner in handling one of their largest financial transactions. But the work is far from over as we continue to grow in new markets. Transforming the real estate industry takes tenacity and dedication. It takes problem solvers and builders. It takes a tight knit community of teammates doing the best work of their lives, pushing one another to transform a complicated process into a simple one. So where do you fit in? Whether you’re passionate about real estate, people, numbers, words, code, or strategy -- we have a place for you. Real estate is broken. Come help us fix it.

About the Team

As a Senior Research Engineer, you will demonstrate data breakthroughs for Opendoor. You will create and develop frameworks and model prototypes that fuel breakthroughs in our ability to model home prices and market trends. Projects can range from step-function algorithmic improvements due to integrating new data sources to partial- or fully algorithmic automation of human processes, driving leveraged operational efficiencies.

Pricing Prediction - Responsible for all the core pricing prediction models, but in particular OVM (which predicts the value of a specific home right now) and HPA (which predicts the value of homes over time). If algorithmic pricing is the heart of Opendoor, this is the heart of algorithmic pricing. You can learn more about OVM, the Opendoor Valuation Model, on our blog.

Role Responsibilities

• Build and evolve models that drive massive customer impact
• Collaborate with research scientists to prototype and productionize improvements to our core valuation model
• Identify opportunities at all stages of the modeling lifecycle, including new models, new data sources, enhancements to models, and rapid feedback loops
• Produce convincing structural and data-driven analyses to falsify ideas or move them forward
• Clearly and concisely articulate the business impact of your work
• Work pragmatically at a high cadence to ship modeling opportunities, such that we generate high learning throughput

Skills Needed

• Extensive experience building production software integrated with machine learning systems
• Knowledge of recent advancements in deep learning, both theoretical and applied
• Experience with container platforms like Docker, and DAG orchestration tools such as AirflowAbility to quickly (1-2 weeks) build proofs of concept and identify the highest-leverage areas to iterate efficiently
• Experience building and deploying production models using deep learning frameworks such as Pytorch or Tensorflow (we use Pytorch + Lightning)
• Strong knowledge of statistics and machine learning
• Highly effective verbal and written communication skills

Bonus points if

• 5+ years of machine learning and generalist engineering experience over a diversity of products
• A risk-aware, investor’s mindset (seeking out and placing bets on a portfolio of projects)
• Experience working with temporal holdout sets in machine learning or statistical models (e.g. time series forecasts)
• A public portfolio of full-stack data products, demos, or blog posts

For CO Residents Only, and in accordance with C.R.S. Sec. 8-5-101 et seq., the estimated base salary range for this role is $145,000 - $232,000 per year. The estimated range is meant to reflect an anticipated salary range for the position in question based upon market data and other factors, all of which are subject to change. Individual pay is based upon location, skills and expertise, experience, and other relevant factors. For questions about this, our pay philosophy, and other available benefits, please speak to the recruiter if you decide to apply for the role and are selected for an interview.