Senior Machine Learning Engineer, Agentic

About Us

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. We are building an elite team, applying frontier technologies to the world's biggest financial problems.

The Role

The Agentic team at Robinhood builds and ships production AI agents that power the next generation of AI financial products. Our mission is to rapidly build, evaluate, and deploy high-performance AI agents on production-grade infrastructure, with strong evaluation and observability baked in, and continuous optimization support.

This role is based in our Menlo Park, CA and Bellevue, WA offices, with in-person attendance expected at least 3 days per week. We believe in the power of in-person work to accelerate progress, spark innovation, and strengthen community.

Responsibilities

• Translate product goals into measurable metrics and SLOs, and build a rigorous evaluation harness to continuously score agents performance
• Develop feedback and optimization pipelines that use both automated metrics and human-in-the-loop evaluation signals to improve agent behavior over time
• Implement and scale optimization techniques such as Direct Preference Optimization (DPO), Proximal Policy Optimization (PPO), and reward modeling to improve agent performance
• Launch and support fine-tuned models in production environments with robust evaluation, rollback strategies, and performance monitoring
• Collaborate closely with applied AI/ML teams to translate state-of-the-art research in agentic reasoning, planning, and tool use into reliable, production-ready systems

Requirements

• Strong technical expertise in software development, with understanding of agentic workflows—including reasoning loops, tool invocation, memory, and orchestration of autonomous AI agents
• Hands-on experience using Large Language Models, including prompt engineering, fine-tuning, model distillation, and deploying optimized models (e.g. via DPO, PPO) into production environments
• Leadership and mentorship capabilities, with a track record of guiding complex technical projects and supporting the growth of teammates through code/design reviews and technical direction
• Excellent communication and collaboration skills, with the ability to translate technical ideas into actionable plans and work effectively with cross-functional partners, including product and infrastructure teams
• Innovation mindset and commitment to continuous learning and a bias toward action, staying at the forefront of ML/AI trends, agentic systems research, and best practices in tooling, safety, and evaluation

Compensation

In addition to the base pay range listed below, this role is also eligible for bonus opportunities, equity, and benefits.

Base pay for the successful applicant will depend on a variety of job-related factors, which may include education, training, experience, location, business needs, or market demands.

Zone 1 (Menlo Park, CA; New York, NY; Bellevue, WA; Washington, DC): $209,000—$245,000 USD

Zone 2 (Denver, CO; Westlake, TX; Chicago, IL): $184,000—$216,000 USD

Zone 3 (Lake Mary, FL; Clearwater, FL; Gainesville, FL): $163,000—$191,000 USD

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
• Best-in-class health insurance including 100% paid health insurance for employees with 90% coverage for dependents
• Lifestyle wallet—a highly flexible benefits spending account for wellness, learning, and more
• Employer-paid life and 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