Open Book: Prasad Seemakurthi, Head of Machine Learning Foundations
Open Book is a series of interviews for you to get to know the incredible people of Opendoor. Meet Prasad, who brings over a decade of experience in tech to his passion for real estate. Learn how he and his team help solve Opendoor’s most complex and impactful data challenges.
Hi Prasad! Thanks for taking the time to talk with us today. Can you share a bit about your career path before joining Opendoor?
I started working in Data Science when it was still a novel idea, especially in India. I was fascinated by how data could help a business, so I enrolled in a satellite certificate program with Carnegie Mellon in New York City. This deepened my interest and validated that there was much to learn. I was working a full-time engineering job at the time but saw this as a path I wanted to pursue — so I quit my job and moved to the U.S. to study Data Science at the University of Virginia.
After earning my graduate degree, I spent over a decade working in different roles across tech companies. My experience spanned startups and then-early companies like Grab, to larger companies, such as American Express. Each role taught me something new, from using the right tools to solve unique problems, to managing big data, scaling technology and programs, and people management. While working at Compass, I began bringing these all skills together and became passionate about solving problems in the real estate industry — and that led me to reach out to Opendoor.
What an incredible journey. When you first joined Opendoor, what did you see as the biggest opportunity?
Previously working in the real estate industry allowed me to become familiar with many of the major players like Opendoor. I noticed that Opendoor was the one business truly empowering all parties in a real estate transaction. I had long thought, “If I can buy a large appliance off Amazon, why can’t I buy a house?” and I loved how Opendoor was able to provide an efficient, ecommerce-like experience. I instantly wanted to be part of building it.
When I reached out to Opendoor, I was invited to meet with several leaders within the company. I had great conversations with Matt Smith, Head of Valuations and Machine Learning Foundations, who later became my manager, and Kushal Chakrabati, Chief Data Officer — confirming we were all trying to solve the same complex challenges. I was also inspired by how empathetic and customer-focused everyone was. I knew joining the team would be a huge opportunity to innovate together.
“Real estate data may not be huge in volume, but it presents some of the most complex challenges to solve.”
Given your diverse experiences at other companies, has anything surprised you about your experience at Opendoor so far?
Having lived in both North America and India working for a variety of companies, I understand how some satellite teams can feel disconnected. But being a part of the team in India at Opendoor isn’t like that — we’re integrated and a true extension of the U.S.-based team. There’s visibility into our work and we have a strong sense of ownership. This healthy environment, paired with strong communication and collaborative discussions about problem-solving, enables everyone to do their best work.
What do you believe sets the engineering and ML practice at Opendoor apart?
At Opendoor, we have both Machine Learning and Research engineering teams. Our researchers leverage data to generate insights, and while they’re not 100% tech-driven, we build the technology to empower their work. As real estate is impacted by macro-headwinds, research is fundamental to the work we do. We ask ourselves things like, “How can this model learn from the past and be ready for events in the future?” Within my team, we’re focused on both explainability and reproducibility to ensure our models will be as durable and efficient as possible.
We’d love to learn more about your role as Head of the Machine Learning Foundations in India. What kinds of projects is your team working on, and where do you see the greatest real-world impact of your efforts?
Our team works on what I call the “bread and butter” of Opendoor. Data is key to solving real estate’s biggest pain points — and we’re driving this practice. Since our founding, we’ve invested heavily in data science, developing the Opendoor Valuation Model to generate home offers. It’s a great example of where our work across platforms, models, and algorithms drives impact. The more accurately we can price homes, the bolder our business bets can be. This unlocks a range of new possibilities, from buying more homes to building an even better customer experience. Real estate is a trillion dollar industry and we have this massive opportunity to create better experiences for millions of buyers and sellers across the country.
Our team in India is growing — we recently announced two new office spaces in Hyderabad and Bengaluru — to give teams a place to innovate and bring fresh perspectives to our products and services. Check out all open roles here and if you’re looking for a Machine Learning opportunity we are hiring a Staff Machine Learning Engineer role in Hyderabad.
How exciting. Are you working on any projects you’re especially excited about right now? We’d love to learn more about them.
While Opendoor already has a functional business and tons of data, there’s an opportunity to apply new learnings and use cases to work we did years ago — helping us find new solutions for the challenges we’re facing.
I’m currently working on a project that will serve as a single source of truth for real estate data across Opendoor. The data sets in real estate are notoriously spotty and erroneous, which is why we’re focused on building the highest quality set of real estate data across homes in the U.S.
You’re a passionate mentor and experienced manager. What do you do to motivate and empower your team amidst a rapidly evolving technology landscape?
My role is about making sure the people on my team have everything they need to do their best work. This also means guiding people through prioritizing and solving impactful problems. For example, I host a quarterly sync with the team where I ask each person to reflect on their work and the next couple of years. Are we focused on the right areas? Are we taking the right approach? What, if anything, could we be doing differently? This constant feedback loop keeps our team aligned and encourages new ways of thinking.
How inspiring. How do you describe opportunities for growth and learning at Opendoor?
We hire when needs arise, so our team’s evolution is fairly organic. With this, learning opportunities are aplenty — we’re working in an exciting space! People who thrive at Opendoor embrace curiosity and love to learn. Our teams deliver real value and we get to see the real-world impact of our efforts every day.
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