Staff Machine Learning Engineer, AI R&D

Robinhood • Menlo Park, CA

10d • Hybrid

About The Position

Robinhood is building an elite team applying frontier technologies to the world's biggest financial problems. The AI R&D team is at the core of Robinhood's product intelligence, focused on building and scaling high-impact models for personalization, search, social feeds, fraud detection, and risk management. This role involves owning the design and delivery of sophisticated personalization and recommendation systems, acting as a technical anchor, collaborating with cross-functional teams, defining technical direction, mentoring engineers, and pushing the boundaries of modern ML, including agentic workflows and LLM fine-tuning, within the fintech industry. The role requires a blend of technical depth, product impact, and innovation, with a focus on building unique systems.

This role is based in Menlo Park, CA and Bellevue, WA offices, with in-person attendance expected at least 3 days per week. Robinhood emphasizes the value of in-person work for accelerating progress, sparking innovation, and strengthening community, with an intentional and energizing office experience designed to support high-performing teams.

Requirements

• 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.

Responsibilities

• 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.

Benefits

• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior