Senior Machine Learning Engineer, Agentic AI

Join us in building the future of finance.

The Agentic AI team builds agentic AI systems that power intelligent, reliable customer experiences across Robinhood products. The team focuses on reducing the time to ship agents with fine‑tuned models and while doing so enables other teams to build, evaluate, and improve their own agents. You will contribute to a culture grounded in first‑principles thinking, high performance, and strong focus on customer outcomes!

As a Senior Machine Learning Engineer (IC5), you will define and uphold the quality bar for agentic systems across the organization. You will design evaluation frameworks, guide model selection, and partner with product, data science, and engineering teams to ensure systems meet clear standards for correctness, safety, latency, and user satisfaction. Your work will shape how agentic systems are built, evaluated, and improved across Robinhood!

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. This role is based in our Bellevue, WA, New York, NY, or Menlo Park, CA office, with in‑person attendance expected at least 3 days per week.

What you’ll do

• Lead the design and evolution of agentic AI systems that power intelligent customer experiences across Robinhood.
• Define the technical direction for evaluating autonomous agents, including reasoning quality, planning, tool selection, memory, task completion, safety, latency, and overall user experience.
• Design and build scalable evaluation frameworks for agentic systems using automated evals, benchmark datasets, LLM‑as‑a‑Judge techniques, and human feedback to continuously improve agent performance.
• Drive model selection and optimization across frontier foundation models, fine‑tuned models, retrieval systems, and tool‑using agents, balancing quality, latency, cost, and reliability.
• Partner closely with Product, Data Science, and Engineering to establish launch criteria, quality standards, and measurable success metrics for production agentic systems.
• Improve agent reliability by investigating production failures, identifying root causes across reasoning, planning, retrieval, and tool execution, and driving architectural improvements.
• Mentor engineers and influence technical direction across teams while helping establish best practices for building reliable, production‑ready agentic AI systems.

What you bring

• Significant experience building and deploying production AI systems powered by large language models, autonomous agents, or multi‑step reasoning workflows.
• Deep understanding of modern agent architectures, including tool calling, planning, memory, retrieval‑augmented generation (RAG), orchestration, and multi‑agent systems.
• Experience designing evaluation frameworks for agentic AI, including automated evals, benchmark datasets, LLM‑as‑a‑Judge methodologies, human evaluation pipelines, and continuous quality measurement.
• Strong understanding of the tradeoffs between prompting, fine‑tuning, retrieval, and agent orchestration, and when to apply each approach.
• Experience evaluating frontier foundation models across quality, latency, safety, cost, robustness, and production readiness.
• Proven ability to debug complex agent behaviors, identify failure modes, and improve reasoning, reliability, and overall system performance.
• Strong software engineering skills with experience building scalable distributed systems and production ML infrastructure.
• Demonstrated technical leadership through architecture design, mentorship, and influencing engineering direction across multiple teams.
• Experience with agent frameworks, AI observability platforms, model evaluation tooling, or regulated AI applications is a strong plus.

What we offer

• 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 benefits to fuel your work, 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 & 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

Base Pay Range

• 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

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. The expected base pay range for this role is based on the location where the work will be performed and is aligned to one of 3 compensation zones. For other locations not listed, compensation can be discussed with your recruiter during the interview process.

Robinhood provides equal opportunity for all applicants, offers reasonable accommodations upon request, and complies with applicable equal employment and privacy laws. Inclusion is built into how we hire and work—welcoming different backgrounds, perspectives, and experiences so everyone can do their best. Please review the Privacy Policy for your country of application.