Senior Machine Learning Engineer

Responsibilities

• Design and build Robinhood’s core agent harness for orchestration, tool integrations, context management, and memory.
• Ship production agentic applications that take real actions for employees and customers.
• Build trajectory-level evaluation systems covering tool-call correctness, planning, recovery, and multi-step task completion.
• Develop simulation environments, synthetic task generation, golden datasets, grading systems, and evaluation data controls.
• Architect action guardrails including tool scoping, permissions, approval gates, blast-radius controls, step and budget limits, sandboxing, and rollback.
• Create SDKs, CI regression gates, continuous red-teaming, and production tracing for adoption by other engineering teams.
• Set technical direction through architecture and code reviews, mentorship, and data-driven decisions about agent readiness.

Requirements

• 10+ years of experience as a Machine Learning Engineer or ML-focused software engineer.
• Strong Python and distributed-systems fundamentals.
• Track record of shipping LLM-powered systems to production at scale.
• Hands-on production experience building agentic systems with tool use, orchestration, context management, and multi-step planning.
• Deep expertise in trajectory-level agent evaluation, tool-call scoring, and simulation environments.
• Expertise designing action-level guardrails, permission and tool-scoping models, approval gates, blast-radius controls, and sandboxing.
• Experience with evaluation methodology including rubric and LLM-as-judge grading, statistical significance, offline-to-online metric correlation, evaluation data versioning, and contamination control.
• Proven ability to build platforms and tooling adopted by other engineering teams.
• Master’s degree in Computer Science or a related technical field, or equivalent professional experience.

Benefits

• Performance-driven compensation with bonus opportunities, equity ownership, and 401(k) matching.
• 100% paid employee health insurance and 90% dependent coverage.
• Employee Fund access for eligible US employees.
• Access to AI tools and continuous AI skill-building.
• Flexible lifestyle wallet for wellness, learning, and other expenses.
• Employer-paid life and disability insurance, fertility benefits, and mental health benefits.
• Company holidays, paid time off, sick time, parental leave, and other time off.
• Catered meals, events, and comfortable office workspaces.
• Based in Menlo Park, California, with in-person attendance expected at least three days per week.