Staff Machine Learning Engineer, AI R&D

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.

The AI R&D team is at the core of Robinhood's product intelligence. Our mission is to build and scale high-impact models that power personalization, search, social feeds, fraud detection, and risk management for millions of Robinhood users. We operate as a cross-functional partner to growth, product, and data engineering—translating complex financial data into intelligent systems that make Robinhood smarter for every customer.

We move fast, raise the bar, and care deeply about building things that matter. If you've ever wanted to solve personalization problems no one else has cracked—in one of the most data-rich, regulated industries on the planet—this is the team for you!

As a Staff Machine Learning Engineer on the AI R&D team, you will own the design and delivery of sophisticated personalization and recommendation systems that directly shape what millions of users see and do on the Robinhood platform. You'll be a technical anchor on a growing, high-caliber team — collaborating with product, data engineering, and fellow ML engineers to take ambitious ideas from zero to one and into production at scale. You'll help define the team's technical direction, mentor engineers, and push the frontier of what's possible when you apply modern ML — including agentic workflows and LLM fine-tuning — to real financial data. This role offers a rare combination of technical depth, product impact, and the satisfaction of building systems that genuinely don't exist anywhere else.

This role is based in our Menlo Park, CA and Bellevue, WA offices, with in-person attendance expected at least 3 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.

• Design, build, and ship end-to-end personalization, ranking, and recommendation systems that power core Robinhood products including growth, social feeds, and search — handling the full ML lifecycle from feature engineering through model deployment and monitoring.
• Partner closely with product, data engineering, and platform teams to define technical strategy, scope complex projects, and drive execution across multiple workstreams simultaneously.
• Lead zero-to-one development of new ML capabilities — prototyping, iterating, and scaling models in a high-stakes fintech environment where data quality and regulatory constraints are first-class concerns.
• Evaluate, experiment with, and integrate modern AI paradigms including agentic workflows and LLM fine-tuning into existing ML systems, pushing the team's technical capabilities forward.
• Set the technical bar through architecture reviews, code reviews, and mentorship — helping to elevate the craft and velocity of the broader AI R&D team.

• 10+ years of experience as a Machine Learning Engineer, with a strong foundation in ML fundamentals (ranking, recommendation systems, deep learning, optimization) and a track record of shipping models to production at scale.
• Demonstrated expertise in personalization and recommendation systems — specifically, experience owning these systems end-to-end in a high-traffic, data-rich environment (fintech, e-commerce, social, or equivalent).
• Proven ability to deliver projects from zero to one: you've taken ambiguous, high-impact problems and built production-grade solutions with measurable results.
• Exposure to or hands-on experience with agentic systems, LLM fine-tuning, or other modern AI paradigms — and the technical judgment to know when (and when not) to apply them.
• A Master's degree in Computer Science, Statistics, or a related technical field, or equivalent professional experience; strong coding skills in Python and familiarity with ML infrastructure tooling.

• Challenging, high-impact work to grow your career
• Performance driven compensation with multipliers for outsized impact, bonus programs, equity ownership, and 401(k) matching
• Top Tier benefits to fuel your work, including 100% paid health insurance for employees with 90% coverage for dependents
• Access to the best AI tools on the market and continuous AI skill-building for every employee, technical or not
• Lifestyle wallet - a highly flexible benefits spending account for wellness, learning, and more
• Employer-paid life & disability insurance, fertility benefits, and mental health benefits
• Time off to recharge including company holidays, paid time off, sick time, parental leave, and more!
• Exceptional office experience with catered meals, events, and comfortable workspaces.