Senior Software Engineer

Join us in building the future of finance.

Our mission

is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history. If you’re ready to be at the epicenter of this historic cultural and financial shift, keep reading.

About the team

+ role We are building an elite team, applying frontier technologies to the world’s biggest financial problems We’re looking for bold thinkers Sharp problem-solvers

Builders who are wired to make an impact Robinhood isn’t a place for complacency, it’s where ambitious people do the best work of their careers We’re a high-performing, fast-moving team with ethics at the center of everything we do

Expectations are high, and so are the rewards Were looking for an exceptional Senior Software Engineer to help shape the future of our core platforms, products, and customer experiences

FinTech is one of the most complex and rapidly evolving spaces in technology, and the challenges were tackling require deep innovation, critical thinking, and scale that dont always have strong precedents.

Youll take on a highly influential role shaping vision and execution across key strategic initiatives Youll partner with cross-functional leaders, contribute to high-impact decisions, guide complex projects from concept to completion, and mentor others on the team

This is a role for someone who leverages modern tools and cutting-edge methodologies as a core part of how they solve problems, and raises the bar for everyone around them.

This role is based in our Menlo Park, CA, with in-person attendance expected at least three days per week.

At Robinhood, we believe in the power of in-person work to accelerate progress, spark innovation, and strengthen community. Our office experience is intentional, energizing, and designed to fully support high-performing teams.

• What youll do Design, develop, and maintain complex machine learning models and AI-powered services that support core product features and decision-making systems. Lead the design and implementation of end-to-end ML pipelines, including data ingestion, feature engineering, model training, evaluation, and deployment. Partner closely with product, data, and engineering teams to translate complex business problems into scalable machine learning solutions. Own ML components end to end, including experimentation, architecture, implementation, deployment, production monitoring, and iteration. Drive improvements in model performance, reliability, and scalability through rigorous experimentation, validation, and optimization.
• Design and