Staff Machine Learning Engineer, Agentic

Unchain Data; Menlo Park (CA); Vor Ort; USD 255.000 - 300.000; Vollzeit

Benefits dieser Stelle

Health insurance

Equity

401(k) matching

Wellness benefits

Life & disability insurance

Paid time off

Zusammenfassung

Robinhood seeks a Staff Machine Learning Engineer (IC6) to 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 standards for correctness, safety, latency, and user satisfaction.

Based in Bellevue, WA or Menlo Park, CA, with in-person attendance required at least 3 days per week, you will shape how agentic systems are built,

Qualifikationen

• Deep experience defining and measuring quality for agentic or ML systems using evaluation frameworks, datasets, and scorecards.
• Experience evaluating large language models or similar systems, including tradeoffs in performance, cost, and latency.
• Demonstrated ability to analyze production issues and lead improvements across multiple teams.
• Comfortable working with engineers, data scientists, and product partners to deliver measurable improvements in system performance.

Aufgaben

• Define and implement evaluation frameworks that measure agent performance, including task success, correctness, tool usage reliability, latency, safety, and user satisfaction
• Evaluate frontier and fine-tuned models across quality, latency, cost, and edge cases to determine appropriate use cases
• Partner with product managers, data scientists, and engineers to translate evaluation results into clear launch criteria for agentic systems
• Analyze production issues, identify root causes, and prioritize improvements to increase system reliability and performance
• Build visibility into agent performance through metrics, monitoring, and reporting that inform roadmap decisions

Kenntnisse

Quality evaluation frameworks

LLM evaluation

Production issue analysis

Cross-functional collaboration

Jobbeschreibung

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. If you're ready to be at the epicenter of this historic cultural and financial shift, we're looking for bold thinkers, sharp problem-solvers, and builders who are wired to make an impact.

About the Role

We are building an elite team applying frontier technologies to the world's biggest financial problems. Robinhood is where ambitious people do the best work of their careers. We're a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards.

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 while enabling other teams to build, evaluate, and improve their own agents.

As a Staff Machine Learning Engineer (IC6), 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.

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

Responsibilities

• Define and implement evaluation frameworks that measure agent performance, including task success, correctness, tool usage reliability, latency, safety, and user satisfaction
• Evaluate frontier and fine-tuned models across quality, latency, cost, and edge cases to determine appropriate use cases
• Partner with product managers, data scientists, and engineers to translate evaluation results into clear launch criteria for agentic systems
• Analyze production issues, identify root causes, and prioritize improvements to increase system reliability and performance
• Build visibility into agent performance through metrics, monitoring, and reporting that inform roadmap decisions

Requirements

• Deep experience defining and measuring quality for agentic or machine learning systems using evaluation frameworks, datasets, and scorecards
• Experience evaluating large language models or similar systems, including understanding tradeoffs in performance, cost, and latency
• Demonstrated ability to analyze production issues and lead initiatives that improve system quality across multiple teams
• Comfortable working with engineers, data scientists, and product partners to deliver measurable improvements in system performance

Nice to Have

• Experience building or operating systems in regulated environments
• Working with AI evaluation and observability tools

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
• 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

Compensation

This role is also eligible for bonus opportunities, equity, and benefits in addition to base pay.

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.

Zone 1 (Menlo Park, CA; New York, NY; Bellevue, WA; Washington, DC)
$255,000 — $300,000 USD

Zone 2 (Denver, CO; Westlake, TX; Chicago, IL)
$225,000 — $264,000 USD

Zone 3 (Lake Mary, FL; Clearwater, FL; Gainesville, FL)
$199,000 — $234,000 USD