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Robinhood is building the foundation for AI agents that power the next generation of AI financial products and internal tools, aiming to democratize finance for all by leveraging frontier technologies to solve the world's biggest financial problems.

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.
• Proven ability to build and scale ML/AI systems, from experimentation to deployment—owning dataset generation, evaluation pipelines, A/B testing, and performance monitoring.

Responsibilities

• Design and create tools and workflows for agent development that support rapid prototyping—define agents, compose toolchains, and construct reasoning loops with minimal overhead.
• Build platform solutions to support scalable experimentation, synthetic dataset generation, and multi-agent evaluation across diverse tasks and domains.
• Develop feedback and optimization pipelines that incorporate both automated metrics and human-in-the-loop evaluation signals to fine-tune agent behavior.
• 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.

Other

• 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.
• The role is located in the office location(s) listed on this job description which will align with our in-office working environment.